Relationship of metabolic syndrome and shoulder OA

Source: https://github.com/markziemann/shoulder-instability-osteroarthritis

Introduction

What is the relationship between metabolic syndrome (visceral obesity, hypertension, elevated fasting glucose, and dyslipidaemia) and the transcriptomic profile of shoulder OA when comparing bone biopsies between patients with cuff arthropathy and primary osteoarthritis? For the above analyses to be effective, we will need to adjust for age, sex and CRP. Patients are classified as having metabolic syndrome = YES, or not = No, giving us a discrete variable which takes into account BMI, Fasting glucose, Cholesterol and Blood pressure in accordance with the international diabetes federation definition.

Also I will conduct a comparison of cuff arth to primary OA control for age sex and CRP.

Load libraries and custom plot functions.

Packages.

suppressPackageStartupMessages({
    library(R.utils)
    library("zoo")
    library("tidyverse")
    library("reshape2")
    library("DESeq2")
    library("gplots")
    library("fgsea")
    library("MASS")
    library("mitch")
    library("eulerr")
    library("limma")
    library("topconfects")
    library("kableExtra")
})

Functions.

maplot <- function(de,contrast_name) {
  sig <-subset(de, padj < 0.05 )
  up <-rownames(subset(de, padj < 0.05 & log2FoldChange > 0))
  dn <-rownames(subset(de, padj < 0.05 & log2FoldChange < 0))
  GENESUP <- length(up)
  GENESDN <- length(dn)
  DET=nrow(de)
  SUBHEADER = paste(GENESUP, "up, ", GENESDN, "down", DET, "detected")
  ns <-subset(de, padj > 0.05 )
  plot(log2(de$baseMean),de$log2FoldChange, 
       xlab="log2 basemean", ylab="log2 foldchange",
       pch=19, cex=0.5, col="dark gray",
       main=contrast_name, cex.main=1)
  points(log2(sig$baseMean),sig$log2FoldChange,
         pch=19, cex=0.5, col="red")
  mtext(SUBHEADER,cex = 1)
}

make_volcano <- function(de,name) {
    sig <- subset(de,padj<0.05)
    N_SIG=nrow(sig)
    N_UP=nrow(subset(sig,log2FoldChange>0))
    N_DN=nrow(subset(sig,log2FoldChange<0))
    DET=nrow(de)
    HEADER=paste(N_SIG,"@5%FDR,", N_UP, "up", N_DN, "dn", DET, "detected")
    plot(de$log2FoldChange,-log10(de$pval),cex=0.5,pch=19,col="darkgray",
        main=name, xlab="log2 FC", ylab="-log10 pval")
    mtext(HEADER)
    grid()
    points(sig$log2FoldChange,-log10(sig$pval),cex=0.5,pch=19,col="red")
}

make_heatmap <- function(de,name,groups,mx,n=30){

  colfunc <- colorRampPalette(c("blue", "white", "red"))
  values <- groups
  f <- colorRamp(c("yellow", "orange"))
  rr <- range(values)
  svals <- (values-rr[1])/diff(rr)
  colcols <- rgb(f(svals)/255)
  mxn <- mx/rowSums(mx)*1000000
  x <- mxn[which(rownames(mxn) %in% rownames(head(de,n))),]
  heatmap.2(as.matrix(x),trace="none",col=colfunc(25),scale="row", margins = c(10,15), cexRow=0.5, 
    main=paste("Top ranked",n,"genes in",name) , ColSideColors = colcols  )

}

Sample sheet

ss <- read.table("pheno_data.tsv",header=TRUE)
rownames(ss) <- sapply(strsplit(ss$fastq,"_R1_"),"[[",1)
rownames(ss) <- gsub("_L001","",rownames(ss))
rownames(ss) <- gsub("-",".",rownames(ss))

ss <- ss[order(rownames(ss)),]

ss %>%
  kbl(caption = "sample sheet") %>%
  kable_paper("hover", full_width = F)

sample sheet

	Participant_ID	Case	Redcap_ID	Tissue	fastq	pvt.pub	Age	Sex	Primary_OA	Cuff_Arthropathy	Prosthesis	Affected_Side	Height_cm	Weight_kg	BMI	ASA	Smoking	Diabetes	Hypercholesterolaemia	Hypertension	Thyroid	CRP	Creat	eGFR	Urea	Fast_Glucose	hba1c	Metabolic_Syndrome	Tendon_integrity_2_years_post.op	ASES_2_years_post.op_Pain	ASES_2_years_post.op_ADL	ASES_2_years_post.op_Total	Oxford_Baseline	Oxford_3_month	Oxford_12_month	Oxford_24_month	QuickDASH_	QuickDASH_3_month	QuickDASH_12_month	QuickDASH_24_month	EQ.5D.3L_Baseline	EQ.5D.3L_3_month	EQ.5D.3L_12_month	EQ.5D.3L_24_month	EQVAS_Baseline	EQVAS_3_month	EQVAS_12_month	EQVAS_24_month
1.1_S41	AD-CAB_3001	RC	53	capsule	1-1_S41_L001_R1_001.fastq.gz	NA	67	M	NA	NA	NA	Left	177.80	120.0	37.90	2	Ever_smoker	No	Yes	Yes	No	2.9	83	84	7.0	5.2	5.6	Yes	Torn	NA	NA	NA	25	41	46	NA	38.6	13.6	13.6	NA	11222	11123	21222	NA	90	50	60	NA
1.2_S67	AD-CAB_3001	RC	53	tendon	1-2_S67_L001_R1_001.fastq.gz	NA	67	M	NA	NA	NA	Left	177.80	120.0	37.90	2	Ever_smoker	No	Yes	Yes	No	2.9	83	84	7.0	5.2	5.6	Yes	Torn	NA	NA	NA	25	41	46	NA	38.6	13.6	13.6	NA	11222	11123	21222	NA	90	50	60	NA
1.3_S93	AD-CAB_3001	RC	53	tear	1-3_S93_L001_R1_001.fastq.gz	NA	67	M	NA	NA	NA	Left	177.80	120.0	37.90	2	Ever_smoker	No	Yes	Yes	No	2.9	83	84	7.0	5.2	5.6	Yes	Torn	NA	NA	NA	25	41	46	NA	38.6	13.6	13.6	NA	11222	11123	21222	NA	90	50	60	NA
10.1_S50	AD-CAB_3010	RC	62	capsule	10-1_S50_L001_R1_001.fastq.gz	NA	58	M	NA	NA	NA	Left	179.00	98.0	30.00	2	Never_smoker	No	No	No	Yes	2.9	82	90	5.6	4.9	5.1	No	Intact	45	17	62	21	45	43	44	45.5	4.5	11.4	20.5	11221	11111	11121	11221	70	70	75	85
10.2_S76	AD-CAB_3010	RC	62	tendon	10-2_S76_L001_R1_001.fastq.gz	NA	58	M	NA	NA	NA	Left	179.00	98.0	30.00	2	Never_smoker	No	No	No	Yes	2.9	82	90	5.6	4.9	5.1	No	Intact	45	17	62	21	45	43	44	45.5	4.5	11.4	20.5	11221	11111	11121	11221	70	70	75	85
10.3_S102	AD-CAB_3010	RC	62	tear	10-3_S102_L001_R1_001.fastq.gz	NA	58	M	NA	NA	NA	Left	179.00	98.0	30.00	2	Never_smoker	No	No	No	Yes	2.9	82	90	5.6	4.9	5.1	No	Intact	45	17	62	21	45	43	44	45.5	4.5	11.4	20.5	11221	11111	11121	11221	70	70	75	85
10B_S21	AD-CAB_4010	OA	90	bone	10B_S21_L001_R1_001.fastq.gz	pvt	80	F	No	Yes	Reverse	Left	161.00	72.0	28.00	2	Never_smoker	No	Yes	No	Yes	11.2	54	86	8.5	7.3	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
10C_S35	AD-CAB_4010	OA	90	capsule	10C_S35_L001_R1_001.fastq.gz	pvt	80	F	No	Yes	Reverse	Left	161.00	72.0	28.00	2	Never_smoker	No	Yes	No	Yes	11.2	54	86	8.5	7.3	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
10S_S49	AD-CAB_4010	OA	90	synovium	10S_S49_L001_R1_001.fastq.gz	pvt	80	F	No	Yes	Reverse	Left	161.00	72.0	28.00	2	Never_smoker	No	Yes	No	Yes	11.2	54	86	8.5	7.3	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
11.1_S51	AD-CAB_3011	RC	63	capsule	11-1_S51_L001_R1_001.fastq.gz	NA	50	M	NA	NA	NA	Right	180.00	82.0	25.00	1	Never_smoker	No	Yes	No	No	2.9	99	76	6.7	5.7	6.0	No	Intact	35	18	53	18	38	44	46	61.4	31.8	6.8	20.5	11221	11222	11111	11121	75	83	75	78
11.2_S77	AD-CAB_3011	RC	63	tendon	11-2_S77_L001_R1_001.fastq.gz	NA	50	M	NA	NA	NA	Right	180.00	82.0	25.00	1	Never_smoker	No	Yes	No	No	2.9	99	76	6.7	5.7	6.0	No	Intact	35	18	53	18	38	44	46	61.4	31.8	6.8	20.5	11221	11222	11111	11121	75	83	75	78
11.3_S103	AD-CAB_3011	RC	63	tear	11-3_S103_L001_R1_001.fastq.gz	NA	50	M	NA	NA	NA	Right	180.00	82.0	25.00	1	Never_smoker	No	Yes	No	No	2.9	99	76	6.7	5.7	6.0	No	Intact	35	18	53	18	38	44	46	61.4	31.8	6.8	20.5	11221	11222	11111	11121	75	83	75	78
11B_S22	AD-CAB_4011	OA	87	bone	11B_S22_L001_R1_001.fastq.gz	pub	76	M	Yes	No	Reverse	Right	180.00	92.0	28.00	2	Never_smoker	No	Yes	Yes	No	4.0	75	85	7.0	6.0	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
11C_S36	AD-CAB_4011	OA	87	capsule	11C_S36_L001_R1_001.fastq.gz	pub	76	M	No	Yes	Reverse	Right	180.00	92.0	28.00	2	Never_smoker	No	Yes	Yes	No	4.0	75	85	7.0	6.0	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
11S_S50	AD-CAB_4011	OA	87	synovium	11S_S50_L001_R1_001.fastq.gz	pub	76	M	Yes	No	Reverse	Right	180.00	92.0	28.00	2	Never_smoker	No	Yes	Yes	No	4.0	75	85	7.0	6.0	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
12.1_S52	AD-CAB_3012	RC	64	capsule	12-1_S52_L001_R1_001.fastq.gz	NA	72	M	NA	NA	NA	Left	173.00	87.0	29.00	3	Never_smoker	Yes	Yes	Yes	No	2.9	108	59	4.8	6.1	6.6	No	NA	50	48	98	29	32	48	42	68.2	0.0	4.5	18.2	12221	11111	11111	11111	70	90	80	90
12.2_S78	AD-CAB_3012	RC	64	tendon	12-2_S78_L001_R1_001.fastq.gz	NA	72	M	NA	NA	NA	Left	173.00	87.0	29.00	3	Never_smoker	Yes	Yes	Yes	No	2.9	108	59	4.8	6.1	6.6	No	NA	50	48	98	29	32	48	42	68.2	0.0	4.5	18.2	12221	11111	11111	11111	70	90	80	90
12.3_S104	AD-CAB_3012	RC	64	tear	12-3_S104_L001_R1_001.fastq.gz	NA	72	M	NA	NA	NA	Left	173.00	87.0	29.00	3	Never_smoker	Yes	Yes	Yes	No	2.9	108	59	4.8	6.1	6.6	No	NA	50	48	98	29	32	48	42	68.2	0.0	4.5	18.2	12221	11111	11111	11111	70	90	80	90
12B_S23	AD-CAB_4012	OA	91	bone	12B_S23_L001_R1_001.fastq.gz	pub	71	F	Yes	No	Anatomic	Right	163.00	83.0	31.00	2	Never_smoker	No	Yes	Yes	No	2.9	73	72	4.8	6.3	5.7	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
12C_S37	AD-CAB_4012	OA	91	capsule	12C_S37_L001_R1_001.fastq.gz	pub	71	F	Yes	No	Anatomic	Right	163.00	83.0	31.00	2	Never_smoker	No	Yes	Yes	No	2.9	73	72	4.8	6.3	5.7	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
12S_S51	AD-CAB_4012	OA	91	synovium	12S_S51_L001_R1_001.fastq.gz	pub	71	F	Yes	No	Anatomic	Right	163.00	83.0	31.00	2	Never_smoker	No	Yes	Yes	No	2.9	73	72	4.8	6.3	5.7	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
13.1_S53	AD-CAB_3013	RC	65	capsule	13-1_S53_L001_R1_001.fastq.gz	NA	68	F	NA	NA	NA	Right	161.00	104.0	40.00	3	Never_smoker	Yes	No	Yes	No	6.3	64	86	6.8	9.2	7.1	Yes	NA	45	45	90	19	34	48	46	75.0	50.0	6.8	2.3	11222	11221	22221	21231	89	78	50	50
13.2_S79	AD-CAB_3013	RC	65	tendon	13-2_S79_L001_R1_001.fastq.gz	NA	68	F	NA	NA	NA	Right	161.00	104.0	40.00	3	Never_smoker	Yes	No	Yes	No	6.3	64	86	6.8	9.2	7.1	Yes	NA	45	45	90	19	34	48	46	75.0	50.0	6.8	2.3	11222	11221	22221	21231	89	78	50	50
13.3_S105	AD-CAB_3013	RC	65	tear	13-3_S105_L001_R1_001.fastq.gz	NA	68	F	NA	NA	NA	Right	161.00	104.0	40.00	3	Never_smoker	Yes	No	Yes	No	6.3	64	86	6.8	9.2	7.1	Yes	NA	45	45	90	19	34	48	46	75.0	50.0	6.8	2.3	11222	11221	22221	21231	89	78	50	50
13B_S24	AD-CAB_4013	OA	89	bone	13B_S24_L001_R1_001.fastq.gz	pvt	69	F	No	Yes	Reverse	Left	170.00	89.0	31.00	2	Never_smoker	No	Yes	Yes	No	2.9	81	85	5.1	5.4	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
13C_S38	AD-CAB_4013	OA	89	capsule	13C_S38_L001_R1_001.fastq.gz	pvt	69	F	No	Yes	Reverse	Left	170.00	89.0	31.00	2	Never_smoker	No	Yes	Yes	No	2.9	81	85	5.1	5.4	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
13S_S52	AD-CAB_4013	OA	89	synovium	13S_S52_L001_R1_001.fastq.gz	pvt	69	F	No	Yes	Reverse	Left	170.00	89.0	31.00	2	Never_smoker	No	Yes	Yes	No	2.9	81	85	5.1	5.4	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
14.1_S54	AD-CAB_3014	RC	66	capsule	14-1_S54_L001_R1_001.fastq.gz	NA	70	M	NA	NA	NA	Left	1.77	100.0	32.00	3	Ever_smoker	No	Yes	Yes	No	2.9	86	79	7.1	6.3	5.8	Yes	Intact	50	45	95	27	43	47	47	50.0	9.1	6.8	9.1	12221	11111	11111	11111	90	90	88	85
14.2_S80	AD-CAB_3014	RC	66	tendon	14-2_S80_L001_R1_001.fastq.gz	NA	70	M	NA	NA	NA	Left	1.77	100.0	32.00	3	Ever_smoker	No	Yes	Yes	No	2.9	86	79	7.1	6.3	5.8	Yes	Intact	50	45	95	27	43	47	47	50.0	9.1	6.8	9.1	12221	11111	11111	11111	90	90	88	85
14.3_S106	AD-CAB_3014	RC	66	tear	14-3_S106_L001_R1_001.fastq.gz	NA	70	M	NA	NA	NA	Left	1.77	100.0	32.00	3	Ever_smoker	No	Yes	Yes	No	2.9	86	79	7.1	6.3	5.8	Yes	Intact	50	45	95	27	43	47	47	50.0	9.1	6.8	9.1	12221	11111	11111	11111	90	90	88	85
14B_S25	AD-CAB_4014	OA	92	bone	14B_S25_L001_R1_001.fastq.gz	pvt	71	M	Yes	No	Reverse	Right	170.00	99.0	34.00	2	Ever_smoker	No	Yes	No	Yes	2.9	69	90	7.0	7.0	7.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
14C_S39	AD-CAB_4014	OA	92	capsule	14C_S39_L001_R1_001.fastq.gz	pvt	71	M	No	Yes	Reverse	Right	170.00	99.0	34.00	2	Ever_smoker	No	Yes	No	Yes	2.9	69	90	7.0	7.0	7.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
14S_S53	AD-CAB_4014	OA	92	synovium	14S_S53_L001_R1_001.fastq.gz	pvt	71	M	Yes	No	Reverse	Right	170.00	99.0	34.00	2	Ever_smoker	No	Yes	No	Yes	2.9	69	90	7.0	7.0	7.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
15.1_S55	AD-CAB_3015	RC	69	capsule	15-1_S55_L001_R1_001.fastq.gz	NA	66	M	NA	NA	NA	Left	175.00	95.0	31.00	3	Never_smoker	No	Yes	Yes	No	2.9	53	90	4.1	5.5	5.2	Yes	Intact	50	47	97	25	NA	NA	48	40.9	NA	NA	13.6	11121	NA	NA	11121	78	NA	NA	93
15.2_S81	AD-CAB_3015	RC	69	tendon	15-2_S81_L001_R1_001.fastq.gz	NA	66	M	NA	NA	NA	Left	175.00	95.0	31.00	3	Never_smoker	No	Yes	Yes	No	2.9	53	90	4.1	5.5	5.2	Yes	Intact	50	47	97	25	NA	NA	48	40.9	NA	NA	13.6	11121	NA	NA	11121	78	NA	NA	93
15.3_S107	AD-CAB_3015	RC	69	tear	15-3_S107_L001_R1_001.fastq.gz	NA	66	M	NA	NA	NA	Left	175.00	95.0	31.00	3	Never_smoker	No	Yes	Yes	No	2.9	53	90	4.1	5.5	5.2	Yes	Intact	50	47	97	25	NA	NA	48	40.9	NA	NA	13.6	11121	NA	NA	11121	78	NA	NA	93
15B_S26	AD-CAB_4015	OA	93	bone	15B_S26_L001_R1_001.fastq.gz	pvt	76	M	Yes	No	Anatomic	Left	183.00	95.0	28.00	2	Ever_smoker	No	Yes	Yes	No	5.6	90	71	6.6	5.5	5.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
15C_S40	AD-CAB_4015	OA	93	capsule	15C_S40_L001_R1_001.fastq.gz	pvt	76	M	Yes	No	Anatomic	Left	183.00	95.0	28.00	2	Ever_smoker	No	Yes	Yes	No	5.6	90	71	6.6	5.5	5.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
15S_S54	AD-CAB_4015	OA	93	synovium	15S_S54_L001_R1_001.fastq.gz	pvt	76	M	Yes	No	Anatomic	Left	183.00	95.0	28.00	2	Ever_smoker	No	Yes	Yes	No	5.6	90	71	6.6	5.5	5.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
16.1_S56	AD-CAB_3016	RC	71	capsule	16-1_S56_L001_R1_001.fastq.gz	NA	68	M	NA	NA	NA	Left	180.00	88.0	27.00	1	Ever_smoker	Yes	No	Yes	No	2.9	73	90	4.7	7.3	8.3	No	Torn	40	42	82	24	27	45	43	43.2	38.6	6.8	11.4	11122	11222	11112	11121	70	60	50	80
16.2_S82	AD-CAB_3016	RC	71	tendon	16-2_S82_L001_R1_001.fastq.gz	NA	68	M	NA	NA	NA	Left	180.00	88.0	27.00	1	Ever_smoker	Yes	No	Yes	No	2.9	73	90	4.7	7.3	8.3	No	Torn	40	42	82	24	27	45	43	43.2	38.6	6.8	11.4	11122	11222	11112	11121	70	60	50	80
16.3_S108	AD-CAB_3016	RC	71	tear	16-3_S108_L001_R1_001.fastq.gz	NA	68	M	NA	NA	NA	Left	180.00	88.0	27.00	1	Ever_smoker	Yes	No	Yes	No	2.9	73	90	4.7	7.3	8.3	No	Torn	40	42	82	24	27	45	43	43.2	38.6	6.8	11.4	11122	11222	11112	11121	70	60	50	80
16B_S27	AD-CAB_4016	OA	99	bone	16B_S27_L001_R1_001.fastq.gz	pvt	76	F	Yes	No	Anatomic	Left	167.00	54.0	19.00	3	Ever_smoker	No	No	No	Yes	2.9	60	86	11.0	4.7	5.3	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
16C_S41	AD-CAB_4016	OA	99	capsule	16C_S41_L001_R1_001.fastq.gz	pvt	76	F	Yes	No	Anatomic	Left	167.00	54.0	19.00	3	Ever_smoker	No	No	No	Yes	2.9	60	86	11.0	4.7	5.3	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
16S_S55	AD-CAB_4016	OA	99	synovium	16S_S55_L001_R1_001.fastq.gz	pvt	76	F	Yes	No	Anatomic	Left	167.00	54.0	19.00	3	Ever_smoker	No	No	No	Yes	2.9	60	86	11.0	4.7	5.3	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
17.1_S57	AD-CAB_3017	RC	70	capsule	17-1_S57_L001_R1_001.fastq.gz	NA	60	M	NA	NA	NA	Left	166.00	80.0	29.00	2	Ever_smoker	No	No	No	No	2.9	119	57	7.2	NA	5.7	No	Torn	NA	NA	NA	13	40	NA	NA	93.2	38.6	NA	NA	12221	21211	NA	NA	70	60	NA	NA
17.2_S83	AD-CAB_3017	RC	70	tendon	17-2_S83_L001_R1_001.fastq.gz	NA	60	M	NA	NA	NA	Left	166.00	80.0	29.00	2	Ever_smoker	No	No	No	No	2.9	119	57	7.2	NA	5.7	No	Torn	NA	NA	NA	13	40	NA	NA	93.2	38.6	NA	NA	12221	21211	NA	NA	70	60	NA	NA
17.3_S109	AD-CAB_3017	RC	70	tear	17-3_S109_L001_R1_001.fastq.gz	NA	60	M	NA	NA	NA	Left	166.00	80.0	29.00	2	Ever_smoker	No	No	No	No	2.9	119	57	7.2	NA	5.7	No	Torn	NA	NA	NA	13	40	NA	NA	93.2	38.6	NA	NA	12221	21211	NA	NA	70	60	NA	NA
17B_S28	AD-CAB_4017	OA	96	bone	17B_S28_L001_R1_001.fastq.gz	pvt	79	F	Yes	No	Reverse	Right	155.00	75.0	31.00	2	Never_smoker	No	No	No	No	9.2	71	70	4.5	5.5	5.1	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
17C_S42	AD-CAB_4017	OA	96	capsule	17C_S42_L001_R1_001.fastq.gz	pvt	79	F	No	Yes	Reverse	Right	155.00	75.0	31.00	2	Never_smoker	No	No	No	No	9.2	71	70	4.5	5.5	5.1	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
17S_S56	AD-CAB_4017	OA	96	synovium	17S_S56_L001_R1_001.fastq.gz	pvt	79	F	Yes	No	Reverse	Right	155.00	75.0	31.00	2	Never_smoker	No	No	No	No	9.2	71	70	4.5	5.5	5.1	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
18.1_S58	AD-CAB_3018	RC	72	capsule	18-1_S58_L001_R1_001.fastq.gz	NA	72	M	NA	NA	NA	Right	170.00	85.0	29.00	2	Ever_smoker	No	Yes	Yes	No	3.2	82	82	6.4	5.5	5.5	No	Intact	50	50	100	36	37	48	48	31.8	13.6	9.1	0.0	11122	11112	11111	11111	90	82	92	90
18.2_S84	AD-CAB_3018	RC	72	tendon	18-2_S84_L001_R1_001.fastq.gz	NA	72	M	NA	NA	NA	Right	170.00	85.0	29.00	2	Ever_smoker	No	Yes	Yes	No	3.2	82	82	6.4	5.5	5.5	No	Intact	50	50	100	36	37	48	48	31.8	13.6	9.1	0.0	11122	11112	11111	11111	90	82	92	90
18.3_S110	AD-CAB_3018	RC	72	tear	18-3_S110_L001_R1_001.fastq.gz	NA	72	M	NA	NA	NA	Right	170.00	85.0	29.00	2	Ever_smoker	No	Yes	Yes	No	3.2	82	82	6.4	5.5	5.5	No	Intact	50	50	100	36	37	48	48	31.8	13.6	9.1	0.0	11122	11112	11111	11111	90	82	92	90
18B_S29	AD-CAB_4018	OA	97	bone	18B_S29_L001_R1_001.fastq.gz	pvt	73	F	Yes	No	Anatomic	Right	167.00	85.0	30.00	3	Ever_smoker	No	Yes	No	No	1.5	78	65	7.3	5.4	5.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
18C_S43	AD-CAB_4018	OA	97	capsule	18C_S43_L001_R1_001.fastq.gz	pvt	73	F	Yes	No	Anatomic	Right	167.00	85.0	30.00	3	Ever_smoker	No	Yes	No	No	1.5	78	65	7.3	5.4	5.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
18S_S57	AD-CAB_4018	OA	97	synovium	18S_S57_L001_R1_001.fastq.gz	pvt	73	F	Yes	No	Anatomic	Right	167.00	85.0	30.00	3	Ever_smoker	No	Yes	No	No	1.5	78	65	7.3	5.4	5.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
19.1_S59	AD-CAB_3019	RC	73	capsule	19-1_S59_L001_R1_001.fastq.gz	NA	45	F	NA	NA	NA	Right	163.00	98.0	36.90	2	Never_smoker	No	Yes	Yes	No	4.3	70	57	4.6	4.7	5.7	Yes	Intact	50	35	85	32	28	45	47	36.4	38.6	18.2	13.6	11221	11221	11121	11121	50	58	45	34
19.2_S85	AD-CAB_3019	RC	73	tendon	19-2_S85_L001_R1_001.fastq.gz	NA	45	F	NA	NA	NA	Right	163.00	98.0	36.90	2	Never_smoker	No	Yes	Yes	No	4.3	70	57	4.6	4.7	5.7	Yes	Intact	50	35	85	32	28	45	47	36.4	38.6	18.2	13.6	11221	11221	11121	11121	50	58	45	34
19.3_S111	AD-CAB_3019	RC	73	tear	19-3_S111_L001_R1_001.fastq.gz	NA	45	F	NA	NA	NA	Right	163.00	98.0	36.90	2	Never_smoker	No	Yes	Yes	No	4.3	70	57	4.6	4.7	5.7	Yes	Intact	50	35	85	32	28	45	47	36.4	38.6	18.2	13.6	11221	11221	11121	11121	50	58	45	34
19B_S30	AD-CAB_4019	OA	95	bone	19B_S30_L001_R1_001.fastq.gz	pvt	65	F	Yes	No	Anatomic	Left	170.00	62.0	21.00	2	Never_smoker	No	No	Yes	No	2.9	103	49	11.0	5.3	5.2	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
19C_S44	AD-CAB_4019	OA	95	capsule	19C_S44_L001_R1_001.fastq.gz	pvt	65	F	Yes	No	Anatomic	Left	170.00	62.0	21.00	2	Never_smoker	No	No	Yes	No	2.9	103	49	11.0	5.3	5.2	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
19S_S58	AD-CAB_4019	OA	95	synovium	19S_S58_L001_R1_001.fastq.gz	pvt	65	F	Yes	No	Anatomic	Left	170.00	62.0	21.00	2	Never_smoker	No	No	Yes	No	2.9	103	49	11.0	5.3	5.2	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
2.1_S42	AD-CAB_3002	RC	54	capsule	2-1_S42_L001_R1_001.fastq.gz	NA	58	M	NA	NA	NA	Right	179.00	79.0	25.00	1	Never_smoker	No	No	No	No	0.7	70	90	6.9	5.4	5.3	No	Torn	NA	NA	NA	33	NA	48	NA	29.5	NA	0.0	NA	11111	NA	11111	NA	90	NA	90	NA
2.2_S68	AD-CAB_3002	RC	54	tendon	2-2_S68_L001_R1_001.fastq.gz	NA	58	M	NA	NA	NA	Right	179.00	79.0	25.00	1	Never_smoker	No	No	No	No	0.7	70	90	6.9	5.4	5.3	No	Torn	NA	NA	NA	33	NA	48	NA	29.5	NA	0.0	NA	11111	NA	11111	NA	90	NA	90	NA
2.3_S94	AD-CAB_3002	RC	54	tear	2-3_S94_L001_R1_001.fastq.gz	NA	58	M	NA	NA	NA	Right	179.00	79.0	25.00	1	Never_smoker	No	No	No	No	0.7	70	90	6.9	5.4	5.3	No	Torn	NA	NA	NA	33	NA	48	NA	29.5	NA	0.0	NA	11111	NA	11111	NA	90	NA	90	NA
20.1_S60	AD-CAB_3020	RC	67	capsule	20-1_S60_L001_R1_001.fastq.gz	NA	61	M	NA	NA	NA	Right	180.00	92.0	29.00	1	Ever_smoker	No	No	No	No	2.9	78	57	3.9	5.5	5.6	No	Intact	50	40	90	30	34	36	44	50.0	34.1	31.8	0.0	12321	12321	12211	12211	77	40	70	70
20.2_S86	AD-CAB_3020	RC	67	tendon	20-2_S86_L001_R1_001.fastq.gz	NA	61	M	NA	NA	NA	Right	180.00	92.0	29.00	1	Ever_smoker	No	No	No	No	2.9	78	57	3.9	5.5	5.6	No	Intact	50	40	90	30	34	36	44	50.0	34.1	31.8	0.0	12321	12321	12211	12211	77	40	70	70
20.3_S112	AD-CAB_3020	RC	67	tear	20-3_S112_L001_R1_001.fastq.gz	NA	61	M	NA	NA	NA	Right	180.00	92.0	29.00	1	Ever_smoker	No	No	No	No	2.9	78	57	3.9	5.5	5.6	No	Intact	50	40	90	30	34	36	44	50.0	34.1	31.8	0.0	12321	12321	12211	12211	77	40	70	70
20B_S31	AD-CAB_4020	OA	98	bone	20B_S31_L001_R1_001.fastq.gz	pvt	62	M	Yes	No	Anatomic	Left	180.00	117.0	36.00	2	Never_smoker	No	Yes	No	No	2.9	80	90	4.9	6.9	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
20C_S45	AD-CAB_4020	OA	98	capsule	20C_S45_L001_R1_001.fastq.gz	pvt	62	M	Yes	No	Anatomic	Left	180.00	117.0	36.00	2	Never_smoker	No	Yes	No	No	2.9	80	90	4.9	6.9	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
20S_S59	AD-CAB_4020	OA	98	synovium	20S_S59_L001_R1_001.fastq.gz	pvt	62	M	Yes	No	Anatomic	Left	180.00	117.0	36.00	2	Never_smoker	No	Yes	No	No	2.9	80	90	4.9	6.9	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
21.1_S61	AD-CAB_3021	RC	68	capsule	21-1_S61_L001_R1_001.fastq.gz	NA	46	M	NA	NA	NA	Right	180.00	88.0	27.20	2	Never_smoker	No	Yes	No	No	2.9	77	57	5.9	5.9	5.3	No	Torn	NA	NA	NA	29	44	43	NA	45.5	20.5	11.4	NA	NA	11111	11121	NA	NA	80	65	NA
21.2_S87	AD-CAB_3021	RC	68	tendon	21-2_S87_L001_R1_001.fastq.gz	NA	46	M	NA	NA	NA	Right	180.00	88.0	27.20	2	Never_smoker	No	Yes	No	No	2.9	77	57	5.9	5.9	5.3	No	Torn	NA	NA	NA	29	44	43	NA	45.5	20.5	11.4	NA	NA	11111	11121	NA	NA	80	65	NA
21.3_S113	AD-CAB_3021	RC	68	tear	21-3_S113_L001_R1_001.fastq.gz	NA	46	M	NA	NA	NA	Right	180.00	88.0	27.20	2	Never_smoker	No	Yes	No	No	2.9	77	57	5.9	5.9	5.3	No	Torn	NA	NA	NA	29	44	43	NA	45.5	20.5	11.4	NA	NA	11111	11121	NA	NA	80	65	NA
22.1_S62	AD-CAB_3022	RC	74	capsule	22-1_S62_L001_R1_001.fastq.gz	NA	39	F	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	25	NA	NA	NA	47.7	NA	NA	NA	12222	NA	NA	NA	30	NA	NA	NA
22.2_S88	AD-CAB_3022	RC	74	tendon	22-2_S88_L001_R1_001.fastq.gz	NA	39	F	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	25	NA	NA	NA	47.7	NA	NA	NA	12222	NA	NA	NA	30	NA	NA	NA
22.3_S114	AD-CAB_3022	RC	74	tear	22-3_S114_L001_R1_001.fastq.gz	NA	39	F	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	25	NA	NA	NA	47.7	NA	NA	NA	12222	NA	NA	NA	30	NA	NA	NA
23.1_S63	AD-CAB_3023	RC	75	capsule	23-1_S63_L001_R1_001.fastq.gz	NA	58	M	NA	NA	NA	Right	179.00	81.0	25.00	2	Ever_smoker	No	Yes	No	No	2.9	75	57	5.7	5.4	5.7	No	Intact	50	40	90	42	43	48	48	15.9	15.9	0.0	2.3	11211	11121	11111	11111	85	85	90	85
23.2_S89	AD-CAB_3023	RC	75	tendon	23-2_S89_L001_R1_001.fastq.gz	NA	58	M	NA	NA	NA	Right	179.00	81.0	25.00	2	Ever_smoker	No	Yes	No	No	2.9	75	57	5.7	5.4	5.7	No	Intact	50	40	90	42	43	48	48	15.9	15.9	0.0	2.3	11211	11121	11111	11111	85	85	90	85
23.3_S115	AD-CAB_3023	RC	75	tear	23-3_S115_L001_R1_001.fastq.gz	NA	58	M	NA	NA	NA	Right	179.00	81.0	25.00	2	Ever_smoker	No	Yes	No	No	2.9	75	57	5.7	5.4	5.7	No	Intact	50	40	90	42	43	48	48	15.9	15.9	0.0	2.3	11211	11121	11111	11111	85	85	90	85
24.1_S64	AD-CAB_3024	RC	76	capsule	24-1_S64_L001_R1_001.fastq.gz	NA	52	F	NA	NA	NA	Right	153.00	70.0	28.00	2	Never_smoker	No	Yes	Yes	Yes	3.0	64	57	7.8	5.6	6.4	No	NA	NA	NA	NA	26	23	NA	NA	56.8	45.5	NA	NA	12222	12221	NA	NA	30	60	NA	NA
24.2_S90	AD-CAB_3024	RC	76	tendon	24-2_S90_L001_R1_001.fastq.gz	NA	52	F	NA	NA	NA	Right	153.00	70.0	28.00	2	Never_smoker	No	Yes	Yes	Yes	3.0	64	57	7.8	5.6	6.4	No	NA	NA	NA	NA	26	23	NA	NA	56.8	45.5	NA	NA	12222	12221	NA	NA	30	60	NA	NA
24.3_S116	AD-CAB_3024	RC	76	tear	24-3_S116_L001_R1_001.fastq.gz	NA	52	F	NA	NA	NA	Right	153.00	70.0	28.00	2	Never_smoker	No	Yes	Yes	Yes	3.0	64	57	7.8	5.6	6.4	No	NA	NA	NA	NA	26	23	NA	NA	56.8	45.5	NA	NA	12222	12221	NA	NA	30	60	NA	NA
25.1_S65	AD-CAB_3025	RC	77	capsule	25-1_S65_L001_R1_001.fastq.gz	NA	62	F	NA	NA	NA	Left	157.00	95.0	38.50	2	Never_smoker	No	Yes	Yes	No	12.0	72	57	6.6	6.2	5.7	Yes	Intact	45	43	88	26	36	38	41	59.1	29.5	31.8	18.2	12231	11221	11221	11121	82	80	60	80
25.2_S91	AD-CAB_3025	RC	77	tendon	25-2_S91_L001_R1_001.fastq.gz	NA	62	F	NA	NA	NA	Left	157.00	95.0	38.50	2	Never_smoker	No	Yes	Yes	No	12.0	72	57	6.6	6.2	5.7	Yes	Intact	45	43	88	26	36	38	41	59.1	29.5	31.8	18.2	12231	11221	11221	11121	82	80	60	80
25.3_S117	AD-CAB_3025	RC	77	tear	25-3_S117_L001_R1_001.fastq.gz	NA	62	F	NA	NA	NA	Left	157.00	95.0	38.50	2	Never_smoker	No	Yes	Yes	No	12.0	72	57	6.6	6.2	5.7	Yes	Intact	45	43	88	26	36	38	41	59.1	29.5	31.8	18.2	12231	11221	11221	11121	82	80	60	80
26.1_S66	AD-CAB_3026	RC	79	capsule	26-1_S66_L001_R1_001.fastq.gz	NA	59	M	NA	NA	NA	Right	176.00	104.0	33.70	2	Ever_smoker	No	Yes	Yes	No	2.9	62	57	4.2	3.6	5.3	Yes	NA	NA	NA	NA	30	42	44	NA	38.6	25.0	22.7	NA	12222	11222	11221	NA	70	90	90	NA
26.2_S92	AD-CAB_3026	RC	79	tendon	26-2_S92_L001_R1_001.fastq.gz	NA	59	M	NA	NA	NA	Right	176.00	104.0	33.70	2	Ever_smoker	No	Yes	Yes	No	2.9	62	57	4.2	3.6	5.3	Yes	NA	NA	NA	NA	30	42	44	NA	38.6	25.0	22.7	NA	12222	11222	11221	NA	70	90	90	NA
26.3_S118	AD-CAB_3026	RC	79	tear	26-3_S118_L001_R1_001.fastq.gz	NA	59	M	NA	NA	NA	Right	176.00	104.0	33.70	2	Ever_smoker	No	Yes	Yes	No	2.9	62	57	4.2	3.6	5.3	Yes	NA	NA	NA	NA	30	42	44	NA	38.6	25.0	22.7	NA	12222	11222	11221	NA	70	90	90	NA
3.1_S43	AD-CAB_3003	RC	55	capsule	3-1_S43_L001_R1_001.fastq.gz	NA	56	M	NA	NA	NA	Left	179.00	85.0	26.52	1	Never_smoker	No	Yes	NA	No	2.9	72	90	4.3	5.2	5.4	No	Intact	50	50	100	38	38	44	48	29.5	27.3	9.1	0.0	11221	11121	11111	22222	80	70	80	60
3.2_S69	AD-CAB_3003	RC	55	tendon	3-2_S69_L001_R1_001.fastq.gz	NA	56	M	NA	NA	NA	Left	179.00	85.0	26.52	1	Never_smoker	No	Yes	NA	No	2.9	72	90	4.3	5.2	5.4	No	Intact	50	50	100	38	38	44	48	29.5	27.3	9.1	0.0	11221	11121	11111	22222	80	70	80	60
3.3_S95	AD-CAB_3003	RC	55	tear	3-3_S95_L001_R1_001.fastq.gz	NA	56	M	NA	NA	NA	Left	179.00	85.0	26.52	1	Never_smoker	No	Yes	NA	No	2.9	72	90	4.3	5.2	5.4	No	Intact	50	50	100	38	38	44	48	29.5	27.3	9.1	0.0	11221	11121	11111	22222	80	70	80	60
4.1_S44	AD-CAB_3004	RC	56	capsule	4-1_S44_L001_R1_001.fastq.gz	NA	68	M	NA	NA	NA	Right	185.00	95.0	28.00	2	Ever_smoker	No	Yes	Yes	No	3.6	91	74	7.8	6.7	5.7	No	Intact	45	50	95	24	41	46	48	NA	18.2	13.6	0.0	11232	11121	11121	11111	NA	80	60	52
4.2_S70	AD-CAB_3004	RC	56	tendon	4-2_S70_L001_R1_001.fastq.gz	NA	68	M	NA	NA	NA	Right	185.00	95.0	28.00	2	Ever_smoker	No	Yes	Yes	No	3.6	91	74	7.8	6.7	5.7	No	Intact	45	50	95	24	41	46	48	NA	18.2	13.6	0.0	11232	11121	11121	11111	NA	80	60	52
4.3_S96	AD-CAB_3004	RC	56	tear	4-3_S96_L001_R1_001.fastq.gz	NA	68	M	NA	NA	NA	Right	185.00	95.0	28.00	2	Ever_smoker	No	Yes	Yes	No	3.6	91	74	7.8	6.7	5.7	No	Intact	45	50	95	24	41	46	48	NA	18.2	13.6	0.0	11232	11121	11121	11111	NA	80	60	52
4001.41B	AD-CAB_4001	OA	84	bone	4001-41B_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	158.00	89.0	36.00	2	Never_smoker	No	Yes	Yes	Yes	2.9	66	82	5.2	5.7	6.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4001.41C	AD-CAB_4001	OA	84	capsule	4001-41C_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	158.00	89.0	36.00	2	Never_smoker	No	Yes	Yes	Yes	2.9	66	82	5.2	5.7	6.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4001.41S	AD-CAB_4001	OA	84	synovium	4001-41S_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	158.00	89.0	36.00	2	Never_smoker	No	Yes	Yes	Yes	2.9	66	82	5.2	5.7	6.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4002.42B	AD-CAB_4002	OA	80	bone	4002-42B_R1_001.fastq.gz	pvt	59	M	Yes	No	Anatomic	Left	182.00	106.0	32.00	1	Ever_smoker	No	Yes	No	No	9.3	69	90	4.3	6.2	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4002.42C	AD-CAB_4002	OA	80	capsule	4002-42C_R1_001.fastq.gz	pvt	59	M	Yes	No	Anatomic	Left	182.00	106.0	32.00	1	Ever_smoker	No	Yes	No	No	9.3	69	90	4.3	6.2	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4002.42S	AD-CAB_4002	OA	80	synovium	4002-42S_R1_001.fastq.gz	pvt	59	M	Yes	No	Anatomic	Left	182.00	106.0	32.00	1	Ever_smoker	No	Yes	No	No	9.3	69	90	4.3	6.2	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4003.43B	AD-CAB_4003	OA	81	bone	4003-43B_R1_001.fastq.gz	pvt	74	F	No	Yes	Reverse	Right	153.00	87.0	37.00	2	Ever_smoker	No	Yes	Yes	No	6.9	77	66	5.0	5.4	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4003.43C	AD-CAB_4003	OA	81	capsule	4003-43C_R1_001.fastq.gz	pvt	74	F	No	Yes	Reverse	Right	153.00	87.0	37.00	2	Ever_smoker	No	Yes	Yes	No	6.9	77	66	5.0	5.4	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4003.43S	AD-CAB_4003	OA	81	synovium	4003-43S_R1_001.fastq.gz	pvt	74	F	No	Yes	Reverse	Right	153.00	87.0	37.00	2	Ever_smoker	No	Yes	Yes	No	6.9	77	66	5.0	5.4	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4004.44B	AD-CAB_4004	OA	82	bone	4004-44B_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	165.00	85.0	32.00	2	Never_smoker	No	Yes	Yes	Yes	3.9	61	89	5.8	5.8	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4004.44C	AD-CAB_4004	OA	82	capsule	4004-44C_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	165.00	85.0	32.00	2	Never_smoker	No	Yes	Yes	Yes	3.9	61	89	5.8	5.8	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4004.44S	AD-CAB_4004	OA	82	synovium	4004-44S_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	165.00	85.0	32.00	2	Never_smoker	No	Yes	Yes	Yes	3.9	61	89	5.8	5.8	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4005.45B	AD-CAB_4005	OA	83	bone	4005-45B_R1_001.fastq.gz	pvt	74	F	Yes	No	Anatomic	Left	169.00	75.0	26.00	2	Ever_smoker	No	Yes	Yes	No	2.9	90	72	6.6	5.2	5.7	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4005.45C	AD-CAB_4005	OA	83	capsule	4005-45C_R1_001.fastq.gz	pvt	74	F	Yes	No	Anatomic	Left	169.00	75.0	26.00	2	Ever_smoker	No	Yes	Yes	No	2.9	90	72	6.6	5.2	5.7	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4005.45S	AD-CAB_4005	OA	83	synovium	4005-45S_R1_001.fastq.gz	pvt	74	F	Yes	No	Anatomic	Left	169.00	75.0	26.00	2	Ever_smoker	No	Yes	Yes	No	2.9	90	72	6.6	5.2	5.7	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4006.46B	AD-CAB_4006	OA	78	bone	4006-46B_R1_001.fastq.gz	pvt	81	F	Yes	No	Anatomic	Right	150.00	54.0	24.00	3	Never_smoker	No	Yes	Yes	No	2.9	105	43	10.5	5.6	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4006.46C	AD-CAB_4006	OA	78	capsule	4006-46C_R1_001.fastq.gz	pvt	81	F	Yes	No	Anatomic	Right	150.00	54.0	24.00	3	Never_smoker	No	Yes	Yes	No	2.9	105	43	10.5	5.6	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4006.46S	AD-CAB_4006	OA	78	synovium	4006-46S_R1_001.fastq.gz	pvt	81	F	Yes	No	Anatomic	Right	150.00	54.0	24.00	3	Never_smoker	No	Yes	Yes	No	2.9	105	43	10.5	5.6	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
5.1_S45	AD-CAB_3005	RC	57	capsule	5-1_S45_L001_R1_001.fastq.gz	NA	59	F	NA	NA	NA	Right	NA	NA	NA	1	Never_smoker	No	No	No	No	3.8	51	90	6.2	NA	5.2	NA	Torn	50	50	100	38	45	NA	48	25.0	4.5	NA	0.0	11121	11111	NA	11111	92	94	95	NA
5.2_S71	AD-CAB_3005	RC	57	tendon	5-2_S71_L001_R1_001.fastq.gz	NA	59	F	NA	NA	NA	Right	NA	NA	NA	1	Never_smoker	No	No	No	No	3.8	51	90	6.2	NA	5.2	NA	Torn	50	50	100	38	45	NA	48	25.0	4.5	NA	0.0	11121	11111	NA	11111	92	94	95	NA
5.3_S97	AD-CAB_3005	RC	57	tear	5-3_S97_L001_R1_001.fastq.gz	NA	59	F	NA	NA	NA	Right	NA	NA	NA	1	Never_smoker	No	No	No	No	3.8	51	90	6.2	NA	5.2	NA	Torn	50	50	100	38	45	NA	48	25.0	4.5	NA	0.0	11121	11111	NA	11111	92	94	95	NA
6.1_S46	AD-CAB_3006	RC	58	capsule	6-1_S46_L001_R1_001.fastq.gz	NA	65	M	NA	NA	NA	Left	172.00	78.0	26.00	1	Never_smoker	No	No	No	No	2.9	77	90	5.6	4.8	5.4	No	Torn	NA	NA	NA	35	31	37	NA	34.1	36.4	27.3	NA	12221	11221	11111	NA	82	40	80	NA
6.2_S72	AD-CAB_3006	RC	58	tendon	6-2_S72_L001_R1_001.fastq.gz	NA	65	M	NA	NA	NA	Left	172.00	78.0	26.00	1	Never_smoker	No	No	No	No	2.9	77	90	5.6	4.8	5.4	No	Torn	NA	NA	NA	35	31	37	NA	34.1	36.4	27.3	NA	12221	11221	11111	NA	82	40	80	NA
6.3_S98	AD-CAB_3006	RC	58	tear	6-3_S98_L001_R1_001.fastq.gz	NA	65	M	NA	NA	NA	Left	172.00	78.0	26.00	1	Never_smoker	No	No	No	No	2.9	77	90	5.6	4.8	5.4	No	Torn	NA	NA	NA	35	31	37	NA	34.1	36.4	27.3	NA	12221	11221	11111	NA	82	40	80	NA
7.1_S47	AD-CAB_3007	RC	59	capsule	7-1_S47_L001_R1_001.fastq.gz	NA	63	F	NA	NA	NA	Right	163.00	57.0	21.50	1	Ever_smoker	No	No	No	No	2.9	53	90	29.0	NA	5.3	No	Intact	50	50	100	37	38	46	48	36.4	18.2	11.4	2.3	11122	11111	11111	11111	93	97	100	100
7.2_S73	AD-CAB_3007	RC	59	tendon	7-2_S73_L001_R1_001.fastq.gz	NA	63	F	NA	NA	NA	Right	163.00	57.0	21.50	1	Ever_smoker	No	No	No	No	2.9	53	90	29.0	NA	5.3	No	Intact	50	50	100	37	38	46	48	36.4	18.2	11.4	2.3	11122	11111	11111	11111	93	97	100	100
7.3_S99	AD-CAB_3007	RC	59	tear	7-3_S99_L001_R1_001.fastq.gz	NA	63	F	NA	NA	NA	Right	163.00	57.0	21.50	1	Ever_smoker	No	No	No	No	2.9	53	90	29.0	NA	5.3	No	Intact	50	50	100	37	38	46	48	36.4	18.2	11.4	2.3	11122	11111	11111	11111	93	97	100	100
7B_S18	AD-CAB_4007	OA	85	bone	7B_S18_L001_R1_001.fastq.gz	pvt	72	M	Yes	No	Anatomic	Right	184.00	118.0	35.00	2	Ever_smoker	No	Yes	Yes	No	12.7	66	90	5.8	5.6	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
7C_S32	AD-CAB_4007	OA	85	capsule	7C_S32_L001_R1_001.fastq.gz	pvt	72	M	Yes	No	Anatomic	Right	184.00	118.0	35.00	2	Ever_smoker	No	Yes	Yes	No	12.7	66	90	5.8	5.6	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
7S_S46	AD-CAB_4007	OA	85	synovium	7S_S46_L001_R1_001.fastq.gz	pvt	72	M	Yes	No	Anatomic	Right	184.00	118.0	35.00	2	Ever_smoker	No	Yes	Yes	No	12.7	66	90	5.8	5.6	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
8.1_S48	AD-CAB_3008	RC	60	capsule	8-1_S48_L001_R1_001.fastq.gz	NA	70	M	NA	NA	NA	Left	167.00	71.0	25.50	2	Never_smoker	No	Yes	Yes	No	2.9	87	77	7.3	5.5	5.4	No	Intact	NA	NA	NA	24	25	47	NA	54.5	54.5	11.4	NA	22221	22221	11111	NA	90	90	92	NA
8.2_S74	AD-CAB_3008	RC	60	tendon	8-2_S74_L001_R1_001.fastq.gz	NA	70	M	NA	NA	NA	Left	167.00	71.0	25.50	2	Never_smoker	No	Yes	Yes	No	2.9	87	77	7.3	5.5	5.4	No	Intact	NA	NA	NA	24	25	47	NA	54.5	54.5	11.4	NA	22221	22221	11111	NA	90	90	92	NA
8.3_S100	AD-CAB_3008	RC	60	tear	8-3_S100_L001_R1_001.fastq.gz	NA	70	M	NA	NA	NA	Left	167.00	71.0	25.50	2	Never_smoker	No	Yes	Yes	No	2.9	87	77	7.3	5.5	5.4	No	Intact	NA	NA	NA	24	25	47	NA	54.5	54.5	11.4	NA	22221	22221	11111	NA	90	90	92	NA
8B_S19	AD-CAB_4008	OA	86	bone	8B_S19_L001_R1_001.fastq.gz	pub	70	M	Yes	No	Anatomic	Right	172.00	86.0	29.00	2	Never_smoker	No	No	Yes	No	2.9	103	64	7.9	5.6	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
8C_S33	AD-CAB_4008	OA	86	capsule	8C_S33_L001_R1_001.fastq.gz	pub	70	M	Yes	No	Anatomic	Right	172.00	86.0	29.00	2	Never_smoker	No	No	Yes	No	2.9	103	64	7.9	5.6	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
8S_S47	AD-CAB_4008	OA	86	synovium	8S_S47_L001_R1_001.fastq.gz	pub	70	M	Yes	No	Anatomic	Right	172.00	86.0	29.00	2	Never_smoker	No	No	Yes	No	2.9	103	64	7.9	5.6	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
9.1_S49	AD-CAB_3009	RC	61	capsule	9-1_S49_L001_R1_001.fastq.gz	NA	68	M	NA	NA	NA	Right	182.00	83.0	25.10	2	Ever_smoker	No	No	No	No	2.9	79	88	7.5	5.8	5.8	No	Intact	50	50	100	35	41	43	46	52.3	11.4	4.5	2.3	11211	11121	11111	11111	85	96	90	90
9.2_S75	AD-CAB_3009	RC	61	tendon	9-2_S75_L001_R1_001.fastq.gz	NA	68	M	NA	NA	NA	Right	182.00	83.0	25.10	2	Ever_smoker	No	No	No	No	2.9	79	88	7.5	5.8	5.8	No	Intact	50	50	100	35	41	43	46	52.3	11.4	4.5	2.3	11211	11121	11111	11111	85	96	90	90
9.3_S101	AD-CAB_3009	RC	61	tear	9-3_S101_L001_R1_001.fastq.gz	NA	68	M	NA	NA	NA	Right	182.00	83.0	25.10	2	Ever_smoker	No	No	No	No	2.9	79	88	7.5	5.8	5.8	No	Intact	50	50	100	35	41	43	46	52.3	11.4	4.5	2.3	11211	11121	11111	11111	85	96	90	90
9B_S20	AD-CAB_4009	OA	88	bone	9B_S20_L001_R1_001.fastq.gz	pvt	72	M	No	Yes	Reverse	Right	167.00	80.0	29.00	3	Ever_smoker	No	Yes	Yes	No	2.9	107	59	6.7	5.8	5.5	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
9C_S34	AD-CAB_4009	OA	88	capsule	9C_S34_L001_R1_001.fastq.gz	pvt	72	M	No	Yes	Reverse	Right	167.00	80.0	29.00	3	Ever_smoker	No	Yes	Yes	No	2.9	107	59	6.7	5.8	5.5	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
9S_S48	AD-CAB_4009	OA	88	synovium	9S_S48_L001_R1_001.fastq.gz	pvt	72	M	No	Yes	Reverse	Right	167.00	80.0	29.00	3	Ever_smoker	No	Yes	Yes	No	2.9	107	59	6.7	5.8	5.5	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SL2.08Re_S60	AD-CAB_4014	OA	92	bone	SL2-08Re_S60_L001_R1_001.fastq.gz	pvt	71	M	Yes	No	Reverse	Right	170.00	99.0	34.00	2	Ever_smoker	No	Yes	No	Yes	2.9	69	90	7.0	7.0	7.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.027_S26	AD-CAB_2001	Insta	27	capsule	SM-027_S26_L001_R1_001.fastq.gz	pub	18	M	NA	NA	NA	Left	188.00	80.0	22.60	2	Ever_smoker	No	No	No	No	5.2	87	90	3.9	4.9	5.4	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.028_S27	AD-CAB_2002	Insta	28	capsule	SM-028_S27_L001_R1_001.fastq.gz	pub	22	F	NA	NA	NA	Right	164.00	73.0	27.10	1	Never_smoker	No	No	No	No	2.9	58	90	3.6	3.4	4.8	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.029_S28	AD-CAB_2003	Insta	29	capsule	SM-029_S28_L001_R1_001.fastq.gz	pvt	21	M	NA	NA	NA	Right	178.00	105.0	33.00	1	Ever_smoker	No	NA	No	Yes	3.0	85	90	5.8	4.3	5.1	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.030_S29	AD-CAB_2004	Insta	30	capsule	SM-030_S29_L001_R1_001.fastq.gz	pvt	19	M	NA	NA	NA	Left	181.00	94.5	29.00	1	Never_smoker	No	No	No	Normal	2.9	69	90	5.7	4.8	5.4	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.031_S30	AD-CAB_2005	Insta	31	capsule	SM-031_S30_L001_R1_001.fastq.gz	NA	27	M	NA	NA	NA	Right	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.032_S31	AD-CAB_2006	Insta	32	capsule	SM-032_S31_L001_R1_001.fastq.gz	pub	19	F	NA	NA	NA	Left	160.00	47.0	18.40	1	Ever_smoker	No	No	No	No	8.2	79	90	3.8	4.2	4.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.033_S32	AD-CAB_2007	Insta	33	capsule	SM-033_S32_L001_R1_001.fastq.gz	pub	18	M	NA	NA	NA	Right	180.00	74.0	22.80	1	Never_smoker	No	NA	No	Yes	2.9	81	90	5.5	6.6	4.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.034_S33	AD-CAB_2008	Insta	34	capsule	SM-034_S33_L001_R1_001.fastq.gz	pub	21	M	NA	NA	NA	Right	195.00	129.0	33.90	1	Never_smoker	No	No	No	No	2.9	96	90	5.9	4.9	4.7	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.035_S34	AD-CAB_2009	Insta	35	capsule	SM-035_S34_L001_R1_001.fastq.gz	pub	18	M	NA	NA	NA	Right	192.00	98.0	26.60	2	Ever_smoker	No	No	No	No	2.9	82	90	4.1	4.6	5.7	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.036_S35	AD-CAB_2010	Insta	36	capsule	SM-036_S35_L001_R1_001.fastq.gz	pub	21	M	NA	NA	NA	Left	180.00	115.0	35.50	2	Ever_smoker	No	No	No	No	3.2	84	90	5.4	4.4	5.3	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.037_S36	AD-CAB_2011	Insta	37	capsule	SM-037_S36_L001_R1_001.fastq.gz	pub	30	M	NA	NA	NA	Left	178.00	82.0	25.90	1	Ever_smoker	No	No	No	No	2.9	94	90	8.2	5.1	5.3	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.038_S37	AD-CAB_2012	Insta	38	capsule	SM-038_S37_L001_R1_001.fastq.gz	pvt	35	M	NA	NA	NA	Left	188.00	75.0	21.20	1	Never_smoker	No	NA	No	No	2.9	106	78	4.7	5.4	5.2	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.039_S38	AD-CAB_2013	Insta	39	capsule	SM-039_S38_L001_R1_001.fastq.gz	pub	21	M	NA	NA	NA	Left	175.00	96.0	31.30	1	Never_smoker	No	No	No	No	NA	93	90	4.1	4.6	4.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.040_S39	AD-CAB_2014	Insta	40	capsule	SM-040_S39_L001_R1_001.fastq.gz	pub	29	M	NA	NA	NA	Right	185.00	105.0	30.70	1	Never_smoker	No	No	No	No	2.9	81	90	6.5	5.0	4.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.041_S40	AD-CAB_2015	Insta	41	capsule	SM-041_S40_L001_R1_001.fastq.gz	pub	23	M	NA	NA	NA	Left	175.00	82.0	26.80	1	Ever_smoker	No	No	No	No	2.9	94	90	4.5	4.1	4.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.042_S41	AD-CAB_2016	Insta	42	capsule	SM-042_S41_L001_R1_001.fastq.gz	pvt	35	M	NA	NA	NA	Right	187.00	80.0	22.90	1	Never_smoker	No	No	No	No	2.9	103	81	4.9	4.5	5.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.043_S42	AD-CAB_2017	Insta	43	capsule	SM-043_S42_L001_R1_001.fastq.gz	pub	19	M	NA	NA	NA	Right	195.00	118.0	31.00	2	Never_smoker	No	No	No	No	2.9	95	90	6.2	4.2	4.5	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.044_S43	AD-CAB_2018	Insta	44	capsule	SM-044_S43_L001_R1_001.fastq.gz	pub	27	M	NA	NA	NA	Right	170.00	82.0	28.40	1	Never_smoker	No	No	No	No	NA	95	90	6.2	5.4	5.5	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.045_S44	AD-CAB_2019	Insta	45	capsule	SM-045_S44_L001_R1_001.fastq.gz	pub	27	M	NA	NA	NA	Left	180.00	76.0	23.50	1	Ever_smoker	No	NA	No	No	2.9	65	90	6.9	4.5	4.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.046_S45	AD-CAB_2020	Insta	46	capsule	SM-046_S45_L001_R1_001.fastq.gz	pub	20	M	NA	NA	NA	Left	181.00	85.0	25.90	1	Never_smoker	No	No	No	No	2.9	105	86	5.8	4.4	5.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.047_S46	AD-CAB_2021	Insta	47	capsule	SM-047_S46_L001_R1_001.fastq.gz	pub	18	M	NA	NA	NA	Left	176.00	65.0	21.00	1	Never_smoker	No	No	No	No	2.9	68	90	4.5	4.3	4.8	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.048_S47	AD-CAB_2022	Insta	48	capsule	SM-048_S47_L001_R1_001.fastq.gz	pvt	32	F	NA	NA	NA	Left	166.00	66.0	24.00	1	Never_smoker	No	NA	No	Yes	2.9	52	90	3.1	4.1	5.3	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.049_S48	AD-CAB_2023	Insta	49	capsule	SM-049_S48_L001_R1_001.fastq.gz	pvt	27	F	NA	NA	NA	Left	170.00	66.0	22.80	1	Never_smoker	No	No	No	No	2.9	91	75	5.5	4.3	4.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.050_S49	AD-CAB_2024	Insta	50	capsule	SM-050_S49_L001_R1_001.fastq.gz	pvt	21	M	NA	NA	NA	Right	189.00	83.0	23.20	1	Never_smoker	No	NA	No	No	2.9	87	90	3.9	4.7	4.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.051_S50	AD-CAB_2025	Insta	51	capsule	SM-051_S50_L001_R1_001.fastq.gz	pvt	21	M	NA	NA	NA	Right	173.00	92.0	31.00	1	Ever_smoker	No	NA	No	No	2.9	71	90	4.1	4.7	5.8	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SM.052_S51	AD-CAB_2026	Insta	52	capsule	SM-052_S51_L001_R1_001.fastq.gz	pub	23	F	NA	NA	NA	Left	169.00	57.0	20.00	2	Ever_smoker	No	No	No	Yes	2.9	68	90	4.5	4.6	5.1	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA

Import read counts

Importing osteoarthritis (OA) and shoulder instability (SI) data separately. Aggregate Lanes together.

if ( !file.exists("counts.rds") ) {
  tmp <- read.table("../fastq/3col.tsv.gz",header=F)
  x <- as.matrix(acast(tmp, V2~V1, value.var="V3", fun.aggregate = sum))
  x <- as.data.frame(x)
  accession <- sapply((strsplit(rownames(x),"\\|")),"[[",2)
  symbol<-sapply((strsplit(rownames(x),"\\|")),"[[",6)
  x$geneid <- paste(accession,symbol)
  xx <- aggregate(. ~ geneid,x,sum)
  rownames(xx) <- xx$geneid
  #colnames <- gsub("T0R","T0",colnames(xx))
  xx$geneid = NULL
  xx <- round(xx)
  txx <- data.frame(t(xx))
  txx$sample <- gsub("_L001","",rownames(txx))
  txx$sample <- gsub("_L002","",txx$sample)
  txx2 <- aggregate(. ~ sample,txx,sum)
  rownames(txx2) <- txx2$sample
  txx2$sample = NULL
  axx <- data.frame(t(txx2))
  axx <- axx[,order(colnames(axx))]
  colnames(axx) <- gsub("^X","",colnames(axx))
  axx <- axx[,order(colnames(axx))]
  remove(tmp,x,xx,txx,txx2)
  gc()
  saveRDS(axx,"counts.rds")
} else {
  axx <- readRDS("counts.rds")
}

Running some checks to ensure that the sample sheet matches the list of datasets.

message("Dimesions of sample sheet:")

## Dimesions of sample sheet:

dim(ss)

## [1] 165  48

message("Dimesions of count matrix:")

## Dimesions of count matrix:

dim(axx)

## [1] 60651   179

message("Number of duplicated samples in the count matrix:")

## Number of duplicated samples in the count matrix:

length(which(duplicated(colnames(axx))))

## [1] 0

message("sample sheet entries with matching datasets")

## sample sheet entries with matching datasets

length(which(rownames(ss) %in% colnames(axx)))

## [1] 165

message("datasets not found in sample sheet")

## datasets not found in sample sheet

colnames(axx)[!colnames(axx) %in% rownames(ss)]

##  [1] "4001.41F"     "4001.41M"     "4002.42F"     "4002.42M"     "4003.43F"    
##  [6] "4003.43M"     "4004.44F"     "4004.44M"     "4005.45F"     "4005.45M"    
## [11] "4006.46F"     "4006.46M"     "SL2.29Re_S61" "SL2.31Re_S62"

There are some datasets not included in the sample sheet so I will ask Sam to get those clinical data so they can be included in future.

QC analysis

Here I’ll look at a few different quality control measures.

par(mar=c(5,8,3,1))
barplot(colSums(axx),horiz=TRUE,las=1,xlab="OA num reads")

sums <- colSums(axx)
sums <- sums[order(sums)]
barplot(sums,horiz=TRUE,las=1,xlab="OA num reads")
abline(v=15000000,col="red")

Some of those read counts are quite low.

MDS plot

Multidimensional scaling plot to show the variation between all samples, very similar to PCA.

mds <- cmdscale(dist(t(axx)))

plot(mds, xlab="Coordinate 1", ylab="Coordinate 2",
  type = "p",bty="n",pch=19, cex=4 ,col="gray")
text(mds, labels=rownames(mds) )

Compare cuff arth to primary OA control for age sex and CRP in bone

Need to:

• select Cuff and OA samples

• select bone datasets only

ss0 <- subset(ss,Cuff_Arthropathy=="Yes" | Primary_OA=="Yes")

ss0b <- subset(ss0,Tissue=="bone")

ss0b %>%
  kbl(caption = "sample sheet for cuff arth vs OA (bone)") %>%
  kable_paper("hover", full_width = F)

sample sheet for cuff arth vs OA (bone)

	Participant_ID	Case	Redcap_ID	Tissue	fastq	pvt.pub	Age	Sex	Primary_OA	Cuff_Arthropathy	Prosthesis	Affected_Side	Height_cm	Weight_kg	BMI	ASA	Smoking	Diabetes	Hypercholesterolaemia	Hypertension	Thyroid	CRP	Creat	eGFR	Urea	Fast_Glucose	hba1c	Metabolic_Syndrome	Tendon_integrity_2_years_post.op	ASES_2_years_post.op_Pain	ASES_2_years_post.op_ADL	ASES_2_years_post.op_Total	Oxford_Baseline	Oxford_3_month	Oxford_12_month	Oxford_24_month	QuickDASH_	QuickDASH_3_month	QuickDASH_12_month	QuickDASH_24_month	EQ.5D.3L_Baseline	EQ.5D.3L_3_month	EQ.5D.3L_12_month	EQ.5D.3L_24_month	EQVAS_Baseline	EQVAS_3_month	EQVAS_12_month	EQVAS_24_month
10B_S21	AD-CAB_4010	OA	90	bone	10B_S21_L001_R1_001.fastq.gz	pvt	80	F	No	Yes	Reverse	Left	161	72	28	2	Never_smoker	No	Yes	No	Yes	11.2	54	86	8.5	7.3	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
11B_S22	AD-CAB_4011	OA	87	bone	11B_S22_L001_R1_001.fastq.gz	pub	76	M	Yes	No	Reverse	Right	180	92	28	2	Never_smoker	No	Yes	Yes	No	4.0	75	85	7.0	6.0	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
12B_S23	AD-CAB_4012	OA	91	bone	12B_S23_L001_R1_001.fastq.gz	pub	71	F	Yes	No	Anatomic	Right	163	83	31	2	Never_smoker	No	Yes	Yes	No	2.9	73	72	4.8	6.3	5.7	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
13B_S24	AD-CAB_4013	OA	89	bone	13B_S24_L001_R1_001.fastq.gz	pvt	69	F	No	Yes	Reverse	Left	170	89	31	2	Never_smoker	No	Yes	Yes	No	2.9	81	85	5.1	5.4	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
14B_S25	AD-CAB_4014	OA	92	bone	14B_S25_L001_R1_001.fastq.gz	pvt	71	M	Yes	No	Reverse	Right	170	99	34	2	Ever_smoker	No	Yes	No	Yes	2.9	69	90	7.0	7.0	7.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
15B_S26	AD-CAB_4015	OA	93	bone	15B_S26_L001_R1_001.fastq.gz	pvt	76	M	Yes	No	Anatomic	Left	183	95	28	2	Ever_smoker	No	Yes	Yes	No	5.6	90	71	6.6	5.5	5.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
16B_S27	AD-CAB_4016	OA	99	bone	16B_S27_L001_R1_001.fastq.gz	pvt	76	F	Yes	No	Anatomic	Left	167	54	19	3	Ever_smoker	No	No	No	Yes	2.9	60	86	11.0	4.7	5.3	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
17B_S28	AD-CAB_4017	OA	96	bone	17B_S28_L001_R1_001.fastq.gz	pvt	79	F	Yes	No	Reverse	Right	155	75	31	2	Never_smoker	No	No	No	No	9.2	71	70	4.5	5.5	5.1	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
18B_S29	AD-CAB_4018	OA	97	bone	18B_S29_L001_R1_001.fastq.gz	pvt	73	F	Yes	No	Anatomic	Right	167	85	30	3	Ever_smoker	No	Yes	No	No	1.5	78	65	7.3	5.4	5.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
19B_S30	AD-CAB_4019	OA	95	bone	19B_S30_L001_R1_001.fastq.gz	pvt	65	F	Yes	No	Anatomic	Left	170	62	21	2	Never_smoker	No	No	Yes	No	2.9	103	49	11.0	5.3	5.2	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
20B_S31	AD-CAB_4020	OA	98	bone	20B_S31_L001_R1_001.fastq.gz	pvt	62	M	Yes	No	Anatomic	Left	180	117	36	2	Never_smoker	No	Yes	No	No	2.9	80	90	4.9	6.9	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4001.41B	AD-CAB_4001	OA	84	bone	4001-41B_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	158	89	36	2	Never_smoker	No	Yes	Yes	Yes	2.9	66	82	5.2	5.7	6.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4002.42B	AD-CAB_4002	OA	80	bone	4002-42B_R1_001.fastq.gz	pvt	59	M	Yes	No	Anatomic	Left	182	106	32	1	Ever_smoker	No	Yes	No	No	9.3	69	90	4.3	6.2	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4003.43B	AD-CAB_4003	OA	81	bone	4003-43B_R1_001.fastq.gz	pvt	74	F	No	Yes	Reverse	Right	153	87	37	2	Ever_smoker	No	Yes	Yes	No	6.9	77	66	5.0	5.4	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4004.44B	AD-CAB_4004	OA	82	bone	4004-44B_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	165	85	32	2	Never_smoker	No	Yes	Yes	Yes	3.9	61	89	5.8	5.8	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4005.45B	AD-CAB_4005	OA	83	bone	4005-45B_R1_001.fastq.gz	pvt	74	F	Yes	No	Anatomic	Left	169	75	26	2	Ever_smoker	No	Yes	Yes	No	2.9	90	72	6.6	5.2	5.7	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4006.46B	AD-CAB_4006	OA	78	bone	4006-46B_R1_001.fastq.gz	pvt	81	F	Yes	No	Anatomic	Right	150	54	24	3	Never_smoker	No	Yes	Yes	No	2.9	105	43	10.5	5.6	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
7B_S18	AD-CAB_4007	OA	85	bone	7B_S18_L001_R1_001.fastq.gz	pvt	72	M	Yes	No	Anatomic	Right	184	118	35	2	Ever_smoker	No	Yes	Yes	No	12.7	66	90	5.8	5.6	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
8B_S19	AD-CAB_4008	OA	86	bone	8B_S19_L001_R1_001.fastq.gz	pub	70	M	Yes	No	Anatomic	Right	172	86	29	2	Never_smoker	No	No	Yes	No	2.9	103	64	7.9	5.6	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
9B_S20	AD-CAB_4009	OA	88	bone	9B_S20_L001_R1_001.fastq.gz	pvt	72	M	No	Yes	Reverse	Right	167	80	29	3	Ever_smoker	No	Yes	Yes	No	2.9	107	59	6.7	5.8	5.5	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SL2.08Re_S60	AD-CAB_4014	OA	92	bone	SL2-08Re_S60_L001_R1_001.fastq.gz	pvt	71	M	Yes	No	Reverse	Right	170	99	34	2	Ever_smoker	No	Yes	No	Yes	2.9	69	90	7.0	7.0	7.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA

message("Metabolic syndrome classification")

## Metabolic syndrome classification

ss0b$Metabolic_Syndrome

##  [1] "No"  "No"  "Yes" "Yes" "Yes" "No"  "No"  "No"  "No"  "No"  "Yes" "Yes"
## [13] "Yes" "Yes" "Yes" "No"  "No"  "Yes" "No"  "No"  "Yes"

message("Age data")

## Age data

ss0b$Age

##  [1] 80 76 71 69 71 76 76 79 73 65 62 69 59 74 69 74 81 72 70 72 71

message("Sex data")

## Sex data

ss0b$Sex

##  [1] "F" "M" "F" "F" "M" "M" "F" "F" "F" "F" "M" "F" "M" "F" "F" "F" "F" "M" "M"
## [20] "M" "M"

x0b <- axx[,colnames(axx) %in% rownames(ss0b)]
message("count matrix dimensions before filtering out low genes")

## count matrix dimensions before filtering out low genes

dim(x0b)

## [1] 60651    21

message("count matrix dimensions after filtering out low genes")

## count matrix dimensions after filtering out low genes

x0b <- x0b[which(rowMeans(x0b)>=10),]
dim(x0b)

## [1] 18383    21

x0b <- x0b[,order(colnames(x0b))]
ss0b <- ss0b[order(rownames(ss0b)),]

ss0b %>%
  kbl(caption = "sample sheet") %>%
  kable_paper("hover", full_width = F)

sample sheet

	Participant_ID	Case	Redcap_ID	Tissue	fastq	pvt.pub	Age	Sex	Primary_OA	Cuff_Arthropathy	Prosthesis	Affected_Side	Height_cm	Weight_kg	BMI	ASA	Smoking	Diabetes	Hypercholesterolaemia	Hypertension	Thyroid	CRP	Creat	eGFR	Urea	Fast_Glucose	hba1c	Metabolic_Syndrome	Tendon_integrity_2_years_post.op	ASES_2_years_post.op_Pain	ASES_2_years_post.op_ADL	ASES_2_years_post.op_Total	Oxford_Baseline	Oxford_3_month	Oxford_12_month	Oxford_24_month	QuickDASH_	QuickDASH_3_month	QuickDASH_12_month	QuickDASH_24_month	EQ.5D.3L_Baseline	EQ.5D.3L_3_month	EQ.5D.3L_12_month	EQ.5D.3L_24_month	EQVAS_Baseline	EQVAS_3_month	EQVAS_12_month	EQVAS_24_month
10B_S21	AD-CAB_4010	OA	90	bone	10B_S21_L001_R1_001.fastq.gz	pvt	80	F	No	Yes	Reverse	Left	161	72	28	2	Never_smoker	No	Yes	No	Yes	11.2	54	86	8.5	7.3	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
11B_S22	AD-CAB_4011	OA	87	bone	11B_S22_L001_R1_001.fastq.gz	pub	76	M	Yes	No	Reverse	Right	180	92	28	2	Never_smoker	No	Yes	Yes	No	4.0	75	85	7.0	6.0	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
12B_S23	AD-CAB_4012	OA	91	bone	12B_S23_L001_R1_001.fastq.gz	pub	71	F	Yes	No	Anatomic	Right	163	83	31	2	Never_smoker	No	Yes	Yes	No	2.9	73	72	4.8	6.3	5.7	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
13B_S24	AD-CAB_4013	OA	89	bone	13B_S24_L001_R1_001.fastq.gz	pvt	69	F	No	Yes	Reverse	Left	170	89	31	2	Never_smoker	No	Yes	Yes	No	2.9	81	85	5.1	5.4	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
14B_S25	AD-CAB_4014	OA	92	bone	14B_S25_L001_R1_001.fastq.gz	pvt	71	M	Yes	No	Reverse	Right	170	99	34	2	Ever_smoker	No	Yes	No	Yes	2.9	69	90	7.0	7.0	7.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
15B_S26	AD-CAB_4015	OA	93	bone	15B_S26_L001_R1_001.fastq.gz	pvt	76	M	Yes	No	Anatomic	Left	183	95	28	2	Ever_smoker	No	Yes	Yes	No	5.6	90	71	6.6	5.5	5.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
16B_S27	AD-CAB_4016	OA	99	bone	16B_S27_L001_R1_001.fastq.gz	pvt	76	F	Yes	No	Anatomic	Left	167	54	19	3	Ever_smoker	No	No	No	Yes	2.9	60	86	11.0	4.7	5.3	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
17B_S28	AD-CAB_4017	OA	96	bone	17B_S28_L001_R1_001.fastq.gz	pvt	79	F	Yes	No	Reverse	Right	155	75	31	2	Never_smoker	No	No	No	No	9.2	71	70	4.5	5.5	5.1	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
18B_S29	AD-CAB_4018	OA	97	bone	18B_S29_L001_R1_001.fastq.gz	pvt	73	F	Yes	No	Anatomic	Right	167	85	30	3	Ever_smoker	No	Yes	No	No	1.5	78	65	7.3	5.4	5.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
19B_S30	AD-CAB_4019	OA	95	bone	19B_S30_L001_R1_001.fastq.gz	pvt	65	F	Yes	No	Anatomic	Left	170	62	21	2	Never_smoker	No	No	Yes	No	2.9	103	49	11.0	5.3	5.2	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
20B_S31	AD-CAB_4020	OA	98	bone	20B_S31_L001_R1_001.fastq.gz	pvt	62	M	Yes	No	Anatomic	Left	180	117	36	2	Never_smoker	No	Yes	No	No	2.9	80	90	4.9	6.9	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4001.41B	AD-CAB_4001	OA	84	bone	4001-41B_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	158	89	36	2	Never_smoker	No	Yes	Yes	Yes	2.9	66	82	5.2	5.7	6.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4002.42B	AD-CAB_4002	OA	80	bone	4002-42B_R1_001.fastq.gz	pvt	59	M	Yes	No	Anatomic	Left	182	106	32	1	Ever_smoker	No	Yes	No	No	9.3	69	90	4.3	6.2	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4003.43B	AD-CAB_4003	OA	81	bone	4003-43B_R1_001.fastq.gz	pvt	74	F	No	Yes	Reverse	Right	153	87	37	2	Ever_smoker	No	Yes	Yes	No	6.9	77	66	5.0	5.4	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4004.44B	AD-CAB_4004	OA	82	bone	4004-44B_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	165	85	32	2	Never_smoker	No	Yes	Yes	Yes	3.9	61	89	5.8	5.8	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4005.45B	AD-CAB_4005	OA	83	bone	4005-45B_R1_001.fastq.gz	pvt	74	F	Yes	No	Anatomic	Left	169	75	26	2	Ever_smoker	No	Yes	Yes	No	2.9	90	72	6.6	5.2	5.7	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4006.46B	AD-CAB_4006	OA	78	bone	4006-46B_R1_001.fastq.gz	pvt	81	F	Yes	No	Anatomic	Right	150	54	24	3	Never_smoker	No	Yes	Yes	No	2.9	105	43	10.5	5.6	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
7B_S18	AD-CAB_4007	OA	85	bone	7B_S18_L001_R1_001.fastq.gz	pvt	72	M	Yes	No	Anatomic	Right	184	118	35	2	Ever_smoker	No	Yes	Yes	No	12.7	66	90	5.8	5.6	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
8B_S19	AD-CAB_4008	OA	86	bone	8B_S19_L001_R1_001.fastq.gz	pub	70	M	Yes	No	Anatomic	Right	172	86	29	2	Never_smoker	No	No	Yes	No	2.9	103	64	7.9	5.6	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
9B_S20	AD-CAB_4009	OA	88	bone	9B_S20_L001_R1_001.fastq.gz	pvt	72	M	No	Yes	Reverse	Right	167	80	29	3	Ever_smoker	No	Yes	Yes	No	2.9	107	59	6.7	5.8	5.5	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SL2.08Re_S60	AD-CAB_4014	OA	92	bone	SL2-08Re_S60_L001_R1_001.fastq.gz	pvt	71	M	Yes	No	Reverse	Right	170	99	34	2	Ever_smoker	No	Yes	No	Yes	2.9	69	90	7.0	7.0	7.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA

plotMDS(x0b)

message("here is the model spec:")

## here is the model spec:

dds <- DESeqDataSetFromMatrix(countData = x0b , colData = ss0b, design = ~ Primary_OA)

## converting counts to integer mode

## Warning in DESeqDataSet(se, design = design, ignoreRank): some variables in
## design formula are characters, converting to factors

res <- DESeq(dds)

## estimating size factors

## estimating dispersions

## gene-wise dispersion estimates

## mean-dispersion relationship

## final dispersion estimates

## fitting model and testing

## -- replacing outliers and refitting for 352 genes
## -- DESeq argument 'minReplicatesForReplace' = 7 
## -- original counts are preserved in counts(dds)

## estimating dispersions

## fitting model and testing

z<- results(res)
vsd <- vst(dds, blind=FALSE)
zz <- cbind(as.data.frame(z),assay(vsd))
dge <- as.data.frame(zz[order(zz$pvalue),])

dge[1:20,1:6] %>%
  kbl(caption = "Top DEGs in bone between cuff arthropathy and OA patients (not correcting for age and sex)") %>%
  kable_paper("hover", full_width = F)

Top DEGs in bone between cuff arthropathy and OA patients (not correcting for age and sex)

	baseMean	log2FoldChange	lfcSE	stat	pvalue	padj
ENSG00000231475.3.IGHV4.31	113.354037	6.9274367	1.3009571	5.324877	0.0000001	0.0018396
ENSG00000160221.18.GATD3A	70.673997	-3.0178695	0.5807588	-5.196425	0.0000002	0.0018498
ENSG00000226065.1.ZBTB45P2	13.633349	5.6825934	1.2070574	4.707807	0.0000025	0.0151990
ENSG00000231187.3.AL356056.2	11.902012	5.4870840	1.1911387	4.606587	0.0000041	0.0186349
ENSG00000184923.12.NUTM2A	20.418626	3.8952646	0.9541063	4.082632	0.0000445	0.1050535
ENSG00000204176.14.SYT15	59.723331	1.4876952	0.3645375	4.081049	0.0000448	0.1050535
ENSG00000237541.4.HLA.DQA2	102.838822	3.4494118	0.8453578	4.080416	0.0000450	0.1050535
ENSG00000233937.7.CTC.338M12.4	33.402510	2.1079769	0.5222860	4.036059	0.0000544	0.1050535
ENSG00000280071.4.GATD3B	437.645856	0.7596460	0.1882586	4.035120	0.0000546	0.1050535
ENSG00000109063.15.MYH3	43.805709	1.1627971	0.2891045	4.022066	0.0000577	0.1050535
ENSG00000115128.7.SF3B6	289.582072	-0.9178741	0.2328682	-3.941604	0.0000809	0.1339901
ENSG00000254395.1.IGHV4.55	72.919096	3.6203414	0.9264473	3.907768	0.0000932	0.1413590
ENSG00000279873.2.LINC01126	9.619567	3.1775559	0.8260587	3.846647	0.0001197	0.1581870
ENSG00000229391.7.HLA.DRB6	26.108495	3.1380284	0.8165895	3.842847	0.0001216	0.1581870
ENSG00000152380.10.FAM151B	26.094286	-1.0863202	0.2952610	-3.679186	0.0002340	0.2667778
ENSG00000083099.11.LYRM2	158.613971	-0.7606543	0.2070305	-3.674117	0.0002387	0.2667778
ENSG00000275464.5.FP565260.1	152.484720	1.1697572	0.3206695	3.647859	0.0002644	0.2667778
ENSG00000105258.9.POLR2I	111.099706	-0.7580720	0.2085126	-3.635616	0.0002773	0.2667778
ENSG00000242861.1.AL591895.1	22.734813	1.7209944	0.4749699	3.623376	0.0002908	0.2667778
ENSG00000169288.18.MRPL1	118.368539	-1.1394894	0.3172411	-3.591872	0.0003283	0.2667778

message("here is the model spec:")

## here is the model spec:

dds <- DESeqDataSetFromMatrix(countData = x0b , colData = ss0b, design = ~ Age + Sex + CRP + Primary_OA )

## converting counts to integer mode

## Warning in DESeqDataSet(se, design = design, ignoreRank): some variables in
## design formula are characters, converting to factors

##   the design formula contains one or more numeric variables with integer values,
##   specifying a model with increasing fold change for higher values.
##   did you mean for this to be a factor? if so, first convert
##   this variable to a factor using the factor() function

##   the design formula contains one or more numeric variables that have mean or
##   standard deviation larger than 5 (an arbitrary threshold to trigger this message).
##   Including numeric variables with large mean can induce collinearity with the intercept.
##   Users should center and scale numeric variables in the design to improve GLM convergence.

res <- DESeq(dds)

## estimating size factors

## estimating dispersions

## gene-wise dispersion estimates

## mean-dispersion relationship

## final dispersion estimates

## fitting model and testing

## 2 rows did not converge in beta, labelled in mcols(object)$betaConv. Use larger maxit argument with nbinomWaldTest

z<- results(res)
vsd <- vst(dds, blind=FALSE)
zz <- cbind(as.data.frame(z),assay(vsd))
dge <- as.data.frame(zz[order(zz$pvalue),])

dge[1:20,1:6] %>%
  kbl(caption = "Top DEGs in bone between cuff arthropathy and OA patients adjusted for age, sex and CRP.") %>%
  kable_paper("hover", full_width = F)

Top DEGs in bone between cuff arthropathy and OA patients adjusted for age, sex and CRP.

	baseMean	log2FoldChange	lfcSE	stat	pvalue	padj
ENSG00000231475.3.IGHV4.31	113.35404	7.691303	1.3877002	5.542482	0.00e+00	0.0005410
ENSG00000280411.1.IGHV1.69D	352.87638	4.073358	0.7512319	5.422238	1.00e-07	0.0005410
ENSG00000160221.18.GATD3A	70.67400	-3.070696	0.5790845	-5.302673	1.00e-07	0.0006993
ENSG00000261796.1.ISY1.RAB43	122.47263	2.575174	0.5688546	4.526946	6.00e-06	0.0244115
ENSG00000211966.2.IGHV5.51	379.90156	4.437549	0.9857874	4.501528	6.70e-06	0.0244115
ENSG00000226065.1.ZBTB45P2	13.63335	5.661125	1.2688283	4.461695	8.10e-06	0.0244115
ENSG00000280071.4.GATD3B	437.64586	0.842649	0.1920091	4.388589	1.14e-05	0.0244115
ENSG00000270550.1.IGHV3.30	929.74531	3.974320	0.9076084	4.378893	1.19e-05	0.0244115
ENSG00000231187.3.AL356056.2	11.90201	5.391960	1.2314707	4.378472	1.20e-05	0.0244115
ENSG00000167476.10.JSRP1	69.52245	2.933264	0.6760584	4.338774	1.43e-05	0.0263392
ENSG00000211970.3.IGHV4.61	204.01512	4.750504	1.1310090	4.200235	2.67e-05	0.0445601
ENSG00000211951.2.IGHV2.26	54.88153	4.409251	1.0601240	4.159184	3.19e-05	0.0473066
ENSG00000236778.8.INTS6.AS1	53.12222	-1.213004	0.2923899	-4.148582	3.35e-05	0.0473066
ENSG00000237541.4.HLA.DQA2	102.83882	3.544540	0.8638749	4.103071	4.08e-05	0.0535342
ENSG00000206341.7.HLA.H	42.42260	2.875753	0.7047631	4.080453	4.49e-05	0.0550853
ENSG00000228049.7.POLR2J2	30.45304	2.618078	0.6458746	4.053539	5.04e-05	0.0579623
ENSG00000211962.2.IGHV1.46	159.03236	3.745839	0.9313057	4.022138	5.77e-05	0.0623642
ENSG00000254395.1.IGHV4.55	72.91910	3.875863	0.9673194	4.006808	6.15e-05	0.0628543
ENSG00000211945.2.IGHV1.18	237.89449	4.064690	1.0220687	3.976924	6.98e-05	0.0643239
ENSG00000184923.12.NUTM2A	20.41863	4.137140	1.0404372	3.976347	7.00e-05	0.0643239

dge0b <- dge

maplot(dge0b,"cuff arthropathy vs OA in bone")

make_volcano(dge0b,"cuff arthropathy vs OA in bone")

make_heatmap(dge0b,"cuff arthropathy vs OA in bone",groups=as.numeric(factor(ss0b$Primary_OA)),x0b,n=50)

Now for cuff arthropathy vs OA in capsule.

ss0 <- subset(ss,Cuff_Arthropathy=="Yes" | Primary_OA=="Yes")

ss0c <- subset(ss0,Tissue=="capsule")

ss0c %>%
  kbl(caption = "sample sheet for cuff arth vs OA (capsule)") %>%
  kable_paper("hover", full_width = F)

sample sheet for cuff arth vs OA (capsule)

	Participant_ID	Case	Redcap_ID	Tissue	fastq	pvt.pub	Age	Sex	Primary_OA	Cuff_Arthropathy	Prosthesis	Affected_Side	Height_cm	Weight_kg	BMI	ASA	Smoking	Diabetes	Hypercholesterolaemia	Hypertension	Thyroid	CRP	Creat	eGFR	Urea	Fast_Glucose	hba1c	Metabolic_Syndrome	Tendon_integrity_2_years_post.op	ASES_2_years_post.op_Pain	ASES_2_years_post.op_ADL	ASES_2_years_post.op_Total	Oxford_Baseline	Oxford_3_month	Oxford_12_month	Oxford_24_month	QuickDASH_	QuickDASH_3_month	QuickDASH_12_month	QuickDASH_24_month	EQ.5D.3L_Baseline	EQ.5D.3L_3_month	EQ.5D.3L_12_month	EQ.5D.3L_24_month	EQVAS_Baseline	EQVAS_3_month	EQVAS_12_month	EQVAS_24_month
10C_S35	AD-CAB_4010	OA	90	capsule	10C_S35_L001_R1_001.fastq.gz	pvt	80	F	No	Yes	Reverse	Left	161	72	28	2	Never_smoker	No	Yes	No	Yes	11.2	54	86	8.5	7.3	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
11C_S36	AD-CAB_4011	OA	87	capsule	11C_S36_L001_R1_001.fastq.gz	pub	76	M	No	Yes	Reverse	Right	180	92	28	2	Never_smoker	No	Yes	Yes	No	4.0	75	85	7.0	6.0	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
12C_S37	AD-CAB_4012	OA	91	capsule	12C_S37_L001_R1_001.fastq.gz	pub	71	F	Yes	No	Anatomic	Right	163	83	31	2	Never_smoker	No	Yes	Yes	No	2.9	73	72	4.8	6.3	5.7	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
13C_S38	AD-CAB_4013	OA	89	capsule	13C_S38_L001_R1_001.fastq.gz	pvt	69	F	No	Yes	Reverse	Left	170	89	31	2	Never_smoker	No	Yes	Yes	No	2.9	81	85	5.1	5.4	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
14C_S39	AD-CAB_4014	OA	92	capsule	14C_S39_L001_R1_001.fastq.gz	pvt	71	M	No	Yes	Reverse	Right	170	99	34	2	Ever_smoker	No	Yes	No	Yes	2.9	69	90	7.0	7.0	7.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
15C_S40	AD-CAB_4015	OA	93	capsule	15C_S40_L001_R1_001.fastq.gz	pvt	76	M	Yes	No	Anatomic	Left	183	95	28	2	Ever_smoker	No	Yes	Yes	No	5.6	90	71	6.6	5.5	5.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
16C_S41	AD-CAB_4016	OA	99	capsule	16C_S41_L001_R1_001.fastq.gz	pvt	76	F	Yes	No	Anatomic	Left	167	54	19	3	Ever_smoker	No	No	No	Yes	2.9	60	86	11.0	4.7	5.3	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
17C_S42	AD-CAB_4017	OA	96	capsule	17C_S42_L001_R1_001.fastq.gz	pvt	79	F	No	Yes	Reverse	Right	155	75	31	2	Never_smoker	No	No	No	No	9.2	71	70	4.5	5.5	5.1	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
18C_S43	AD-CAB_4018	OA	97	capsule	18C_S43_L001_R1_001.fastq.gz	pvt	73	F	Yes	No	Anatomic	Right	167	85	30	3	Ever_smoker	No	Yes	No	No	1.5	78	65	7.3	5.4	5.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
19C_S44	AD-CAB_4019	OA	95	capsule	19C_S44_L001_R1_001.fastq.gz	pvt	65	F	Yes	No	Anatomic	Left	170	62	21	2	Never_smoker	No	No	Yes	No	2.9	103	49	11.0	5.3	5.2	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
20C_S45	AD-CAB_4020	OA	98	capsule	20C_S45_L001_R1_001.fastq.gz	pvt	62	M	Yes	No	Anatomic	Left	180	117	36	2	Never_smoker	No	Yes	No	No	2.9	80	90	4.9	6.9	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4001.41C	AD-CAB_4001	OA	84	capsule	4001-41C_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	158	89	36	2	Never_smoker	No	Yes	Yes	Yes	2.9	66	82	5.2	5.7	6.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4002.42C	AD-CAB_4002	OA	80	capsule	4002-42C_R1_001.fastq.gz	pvt	59	M	Yes	No	Anatomic	Left	182	106	32	1	Ever_smoker	No	Yes	No	No	9.3	69	90	4.3	6.2	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4003.43C	AD-CAB_4003	OA	81	capsule	4003-43C_R1_001.fastq.gz	pvt	74	F	No	Yes	Reverse	Right	153	87	37	2	Ever_smoker	No	Yes	Yes	No	6.9	77	66	5.0	5.4	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4004.44C	AD-CAB_4004	OA	82	capsule	4004-44C_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	165	85	32	2	Never_smoker	No	Yes	Yes	Yes	3.9	61	89	5.8	5.8	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4005.45C	AD-CAB_4005	OA	83	capsule	4005-45C_R1_001.fastq.gz	pvt	74	F	Yes	No	Anatomic	Left	169	75	26	2	Ever_smoker	No	Yes	Yes	No	2.9	90	72	6.6	5.2	5.7	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4006.46C	AD-CAB_4006	OA	78	capsule	4006-46C_R1_001.fastq.gz	pvt	81	F	Yes	No	Anatomic	Right	150	54	24	3	Never_smoker	No	Yes	Yes	No	2.9	105	43	10.5	5.6	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
7C_S32	AD-CAB_4007	OA	85	capsule	7C_S32_L001_R1_001.fastq.gz	pvt	72	M	Yes	No	Anatomic	Right	184	118	35	2	Ever_smoker	No	Yes	Yes	No	12.7	66	90	5.8	5.6	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
8C_S33	AD-CAB_4008	OA	86	capsule	8C_S33_L001_R1_001.fastq.gz	pub	70	M	Yes	No	Anatomic	Right	172	86	29	2	Never_smoker	No	No	Yes	No	2.9	103	64	7.9	5.6	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
9C_S34	AD-CAB_4009	OA	88	capsule	9C_S34_L001_R1_001.fastq.gz	pvt	72	M	No	Yes	Reverse	Right	167	80	29	3	Ever_smoker	No	Yes	Yes	No	2.9	107	59	6.7	5.8	5.5	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA

message("Metabolic syndrome classification")

## Metabolic syndrome classification

ss0c$Metabolic_Syndrome

##  [1] "No"  "No"  "Yes" "Yes" "Yes" "No"  "No"  "No"  "No"  "No"  "Yes" "Yes"
## [13] "Yes" "Yes" "Yes" "No"  "No"  "Yes" "No"  "No"

message("Age data")

## Age data

ss0c$Age

##  [1] 80 76 71 69 71 76 76 79 73 65 62 69 59 74 69 74 81 72 70 72

message("Sex data")

## Sex data

ss0c$Sex

##  [1] "F" "M" "F" "F" "M" "M" "F" "F" "F" "F" "M" "F" "M" "F" "F" "F" "F" "M" "M"
## [20] "M"

x0c <- axx[,colnames(axx) %in% rownames(ss0c)]
message("count matrix dimensions before filtering out low genes")

## count matrix dimensions before filtering out low genes

dim(x0c)

## [1] 60651    20

x0c <- x0c[which(rowMeans(x0c)>=10),]
message("count matrix dimensions after filtering out low genes")

## count matrix dimensions after filtering out low genes

dim(x0c)

## [1] 17340    20

x0c <- x0c[,order(colnames(x0c))]
ss0c <- ss0c[order(rownames(ss0c)),]

plotMDS(x0c)

message("here is the model spec:")

## here is the model spec:

dds <- DESeqDataSetFromMatrix(countData = x0c , colData = ss0c, design = ~ Primary_OA)

## converting counts to integer mode

## Warning in DESeqDataSet(se, design = design, ignoreRank): some variables in
## design formula are characters, converting to factors

res <- DESeq(dds)

## estimating size factors

## estimating dispersions

## gene-wise dispersion estimates

## mean-dispersion relationship

## final dispersion estimates

## fitting model and testing

## -- replacing outliers and refitting for 94 genes
## -- DESeq argument 'minReplicatesForReplace' = 7 
## -- original counts are preserved in counts(dds)

## estimating dispersions

## fitting model and testing

z<- results(res)
vsd <- vst(dds, blind=FALSE)
zz <- cbind(as.data.frame(z),assay(vsd))
dge <- as.data.frame(zz[order(zz$pvalue),])
dge[1:20,1:6] %>%
  kbl(caption = "Top DEGs in bone between cuff arthropathy and OA patients (not correcting for age and sex)") %>%
  kable_paper("hover", full_width = F)

Top DEGs in bone between cuff arthropathy and OA patients (not correcting for age and sex)

	baseMean	log2FoldChange	lfcSE	stat	pvalue	padj
ENSG00000160221.18.GATD3A	82.776968	-2.6902133	0.4897308	-5.493249	0.0000000	0.0006842
ENSG00000175084.12.DES	130.464566	1.9970130	0.4913189	4.064596	0.0000481	0.3768375
ENSG00000241322.11.CDRT1	12.715250	-1.9852864	0.5046605	-3.933905	0.0000836	0.3768375
ENSG00000179935.10.LINC00652	14.262009	-1.4152755	0.3693240	-3.832070	0.0001271	0.3768375
ENSG00000114854.8.TNNC1	33.941783	2.9962035	0.7880244	3.802171	0.0001434	0.3768375
ENSG00000205054.8.LINC01121	10.112682	-1.6777326	0.4518356	-3.713148	0.0002047	0.3768375
ENSG00000261776.1.AC079414.2	15.868365	-2.4479813	0.6642446	-3.685361	0.0002284	0.3768375
ENSG00000197124.12.ZNF682	30.667027	1.1089760	0.3009262	3.685209	0.0002285	0.3768375
ENSG00000002745.13.WNT16	38.834851	-4.2622131	1.1573304	-3.682797	0.0002307	0.3768375
ENSG00000125912.11.NCLN	430.132352	0.3500618	0.0969839	3.609483	0.0003068	0.3768375
ENSG00000133063.16.CHIT1	41.560145	-2.0428240	0.5659999	-3.609230	0.0003071	0.3768375
ENSG00000135127.11.BICDL1	17.614776	-1.4165583	0.3939113	-3.596135	0.0003230	0.3768375
ENSG00000135622.13.SEMA4F	116.995538	0.5513237	0.1535505	3.590505	0.0003300	0.3768375
ENSG00000255458.7.AC108471.2	11.769050	-1.8054217	0.5029325	-3.589789	0.0003309	0.3768375
ENSG00000248144.6.ADH1C	20.718223	2.7621798	0.7696270	3.588985	0.0003320	0.3768375
ENSG00000151338.18.MIPOL1	46.069885	-0.9191058	0.2576117	-3.567795	0.0003600	0.3768375
ENSG00000199753.1.SNORD104	22.793485	1.0002137	0.2835392	3.527602	0.0004193	0.3768375
ENSG00000154645.14.CHODL	9.613827	-3.2310250	0.9205096	-3.510039	0.0004480	0.3768375
ENSG00000183054.12.RGPD6	102.597304	2.1690933	0.6180938	3.509327	0.0004492	0.3768375
ENSG00000163607.17.GTPBP8	53.948796	-0.5705045	0.1629093	-3.501976	0.0004618	0.3768375

message("here is the model spec:")

## here is the model spec:

dds <- DESeqDataSetFromMatrix(countData = x0c , colData = ss0c, design = ~ Age + Sex + CRP + Primary_OA )

## converting counts to integer mode

## Warning in DESeqDataSet(se, design = design, ignoreRank): some variables in
## design formula are characters, converting to factors

##   the design formula contains one or more numeric variables with integer values,
##   specifying a model with increasing fold change for higher values.
##   did you mean for this to be a factor? if so, first convert
##   this variable to a factor using the factor() function

##   the design formula contains one or more numeric variables that have mean or
##   standard deviation larger than 5 (an arbitrary threshold to trigger this message).
##   Including numeric variables with large mean can induce collinearity with the intercept.
##   Users should center and scale numeric variables in the design to improve GLM convergence.

res <- DESeq(dds)

## estimating size factors

## estimating dispersions

## gene-wise dispersion estimates

## mean-dispersion relationship

## final dispersion estimates

## fitting model and testing

## 2 rows did not converge in beta, labelled in mcols(object)$betaConv. Use larger maxit argument with nbinomWaldTest

z<- results(res)
vsd <- vst(dds, blind=FALSE)
zz <- cbind(as.data.frame(z),assay(vsd))
dge <- as.data.frame(zz[order(zz$pvalue),])

dge[1:20,1:6] %>%
  kbl(caption = "Top DEGs in bone between cuff arthropathy and OA patients adjusted for age, sex and CRP.") %>%
  kable_paper("hover", full_width = F)

Top DEGs in bone between cuff arthropathy and OA patients adjusted for age, sex and CRP.

	baseMean	log2FoldChange	lfcSE	stat	pvalue	padj
ENSG00000160221.18.GATD3A	82.77697	-2.8201856	0.5165101	-5.460079	0.0000000	0.0008253
ENSG00000241322.11.CDRT1	12.71525	-2.2904291	0.5623498	-4.072961	0.0000464	0.2588321
ENSG00000261776.1.AC079414.2	15.86836	-2.8887873	0.7313977	-3.949681	0.0000783	0.2588321
ENSG00000175084.12.DES	130.46457	1.8294800	0.4644204	3.939276	0.0000817	0.2588321
ENSG00000284722.2.AP003175.1	14.98458	-2.2330722	0.5694452	-3.921487	0.0000880	0.2588321
ENSG00000239704.11.CDRT4	71.06216	0.9557273	0.2448747	3.902924	0.0000950	0.2588321
ENSG00000255458.7.AC108471.2	11.76905	-2.0403979	0.5258858	-3.879926	0.0001045	0.2588321
ENSG00000130368.7.MAS1	20.09030	-2.3785438	0.6225289	-3.820776	0.0001330	0.2883475
ENSG00000269600.2.AC016629.2	17.06060	-1.8487647	0.5015056	-3.686428	0.0002274	0.3150250
ENSG00000005187.12.ACSM3	19.13072	-1.7109043	0.4642966	-3.684938	0.0002288	0.3150250
ENSG00000244040.7.IL12A.AS1	12.56259	-2.2720054	0.6236527	-3.643062	0.0002694	0.3150250
ENSG00000205930.10.C21orf62.AS1	41.39002	-1.3878887	0.3838506	-3.615700	0.0002995	0.3150250
ENSG00000205054.8.LINC01121	10.11268	-1.8717111	0.5179307	-3.613825	0.0003017	0.3150250
ENSG00000279085.1.AL022323.2	16.16489	-2.3579100	0.6532940	-3.609263	0.0003071	0.3150250
ENSG00000244128.7.LINC01322	19.80602	-2.7691623	0.7686080	-3.602828	0.0003148	0.3150250
ENSG00000261052.6.SULT1A3	152.76977	1.2454267	0.3457351	3.602257	0.0003155	0.3150250
ENSG00000260876.6.LINC01229	11.75654	-1.5291981	0.4251893	-3.596511	0.0003225	0.3150250
ENSG00000224810.1.AL355482.1	19.28433	-2.2142403	0.6163669	-3.592406	0.0003276	0.3150250
ENSG00000002745.13.WNT16	38.83485	-3.6505808	1.0233230	-3.567379	0.0003606	0.3150250
ENSG00000280071.4.GATD3B	468.23472	0.6112931	0.1714532	3.565365	0.0003634	0.3150250

dge0c <- dge

maplot(dge0c,"cuff arthropathy vs OA in capsule")

make_volcano(dge0c,"cuff arthropathy vs OA in capsule")

make_heatmap(dge0c,"cuff arthropathy vs OA in capsule",groups=as.numeric(factor(ss0b$Primary_OA)),x0b,n=50)

The effect of metabolic syndrome in OA

Need to:

• select bone datasets only

• select OA samples only

• look at the effect of metabolic syndrome in OA (ss1).

ss1 <- subset(ss,Primary_OA=="Yes")

ss1b <- subset(ss1,Tissue=="bone")

message("Metabolic syndrome classification")

## Metabolic syndrome classification

ss1b$Metabolic_Syndrome

##  [1] "No"  "Yes" "Yes" "No"  "No"  "No"  "No"  "No"  "Yes" "Yes" "Yes" "Yes"
## [13] "No"  "No"  "Yes" "No"  "Yes"

message("Age data")

## Age data

ss1b$Age

##  [1] 76 71 71 76 76 79 73 65 62 69 59 69 74 81 72 70 71

message("Sex data")

## Sex data

ss1b$Sex

##  [1] "M" "F" "M" "M" "F" "F" "F" "F" "M" "F" "M" "F" "F" "F" "M" "M" "M"

x1b <- axx[,colnames(axx) %in% rownames(ss1b)]
message("count matrix dimensions before filtering out low genes")

## count matrix dimensions before filtering out low genes

dim(x1b)

## [1] 60651    17

x1b <- x1b[which(rowMeans(x1b)>=10),]
message("count matrix dimensions after filtering out low genes")

## count matrix dimensions after filtering out low genes

dim(x1b)

## [1] 18412    17

x1b <- x1b[,order(colnames(x1b))]
ss1b <- ss1b[order(rownames(ss1b)),]

ss1b %>%
  kbl(caption = "sample sheet") %>%
  kable_paper("hover", full_width = F)

sample sheet

	Participant_ID	Case	Redcap_ID	Tissue	fastq	pvt.pub	Age	Sex	Primary_OA	Cuff_Arthropathy	Prosthesis	Affected_Side	Height_cm	Weight_kg	BMI	ASA	Smoking	Diabetes	Hypercholesterolaemia	Hypertension	Thyroid	CRP	Creat	eGFR	Urea	Fast_Glucose	hba1c	Metabolic_Syndrome	Tendon_integrity_2_years_post.op	ASES_2_years_post.op_Pain	ASES_2_years_post.op_ADL	ASES_2_years_post.op_Total	Oxford_Baseline	Oxford_3_month	Oxford_12_month	Oxford_24_month	QuickDASH_	QuickDASH_3_month	QuickDASH_12_month	QuickDASH_24_month	EQ.5D.3L_Baseline	EQ.5D.3L_3_month	EQ.5D.3L_12_month	EQ.5D.3L_24_month	EQVAS_Baseline	EQVAS_3_month	EQVAS_12_month	EQVAS_24_month
11B_S22	AD-CAB_4011	OA	87	bone	11B_S22_L001_R1_001.fastq.gz	pub	76	M	Yes	No	Reverse	Right	180	92	28	2	Never_smoker	No	Yes	Yes	No	4.0	75	85	7.0	6.0	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
12B_S23	AD-CAB_4012	OA	91	bone	12B_S23_L001_R1_001.fastq.gz	pub	71	F	Yes	No	Anatomic	Right	163	83	31	2	Never_smoker	No	Yes	Yes	No	2.9	73	72	4.8	6.3	5.7	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
14B_S25	AD-CAB_4014	OA	92	bone	14B_S25_L001_R1_001.fastq.gz	pvt	71	M	Yes	No	Reverse	Right	170	99	34	2	Ever_smoker	No	Yes	No	Yes	2.9	69	90	7.0	7.0	7.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
15B_S26	AD-CAB_4015	OA	93	bone	15B_S26_L001_R1_001.fastq.gz	pvt	76	M	Yes	No	Anatomic	Left	183	95	28	2	Ever_smoker	No	Yes	Yes	No	5.6	90	71	6.6	5.5	5.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
16B_S27	AD-CAB_4016	OA	99	bone	16B_S27_L001_R1_001.fastq.gz	pvt	76	F	Yes	No	Anatomic	Left	167	54	19	3	Ever_smoker	No	No	No	Yes	2.9	60	86	11.0	4.7	5.3	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
17B_S28	AD-CAB_4017	OA	96	bone	17B_S28_L001_R1_001.fastq.gz	pvt	79	F	Yes	No	Reverse	Right	155	75	31	2	Never_smoker	No	No	No	No	9.2	71	70	4.5	5.5	5.1	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
18B_S29	AD-CAB_4018	OA	97	bone	18B_S29_L001_R1_001.fastq.gz	pvt	73	F	Yes	No	Anatomic	Right	167	85	30	3	Ever_smoker	No	Yes	No	No	1.5	78	65	7.3	5.4	5.9	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
19B_S30	AD-CAB_4019	OA	95	bone	19B_S30_L001_R1_001.fastq.gz	pvt	65	F	Yes	No	Anatomic	Left	170	62	21	2	Never_smoker	No	No	Yes	No	2.9	103	49	11.0	5.3	5.2	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
20B_S31	AD-CAB_4020	OA	98	bone	20B_S31_L001_R1_001.fastq.gz	pvt	62	M	Yes	No	Anatomic	Left	180	117	36	2	Never_smoker	No	Yes	No	No	2.9	80	90	4.9	6.9	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4001.41B	AD-CAB_4001	OA	84	bone	4001-41B_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	158	89	36	2	Never_smoker	No	Yes	Yes	Yes	2.9	66	82	5.2	5.7	6.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4002.42B	AD-CAB_4002	OA	80	bone	4002-42B_R1_001.fastq.gz	pvt	59	M	Yes	No	Anatomic	Left	182	106	32	1	Ever_smoker	No	Yes	No	No	9.3	69	90	4.3	6.2	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4004.44B	AD-CAB_4004	OA	82	bone	4004-44B_R1_001.fastq.gz	pvt	69	F	Yes	No	Anatomic	Left	165	85	32	2	Never_smoker	No	Yes	Yes	Yes	3.9	61	89	5.8	5.8	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4005.45B	AD-CAB_4005	OA	83	bone	4005-45B_R1_001.fastq.gz	pvt	74	F	Yes	No	Anatomic	Left	169	75	26	2	Ever_smoker	No	Yes	Yes	No	2.9	90	72	6.6	5.2	5.7	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4006.46B	AD-CAB_4006	OA	78	bone	4006-46B_R1_001.fastq.gz	pvt	81	F	Yes	No	Anatomic	Right	150	54	24	3	Never_smoker	No	Yes	Yes	No	2.9	105	43	10.5	5.6	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
7B_S18	AD-CAB_4007	OA	85	bone	7B_S18_L001_R1_001.fastq.gz	pvt	72	M	Yes	No	Anatomic	Right	184	118	35	2	Ever_smoker	No	Yes	Yes	No	12.7	66	90	5.8	5.6	5.6	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
8B_S19	AD-CAB_4008	OA	86	bone	8B_S19_L001_R1_001.fastq.gz	pub	70	M	Yes	No	Anatomic	Right	172	86	29	2	Never_smoker	No	No	Yes	No	2.9	103	64	7.9	5.6	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
SL2.08Re_S60	AD-CAB_4014	OA	92	bone	SL2-08Re_S60_L001_R1_001.fastq.gz	pvt	71	M	Yes	No	Reverse	Right	170	99	34	2	Ever_smoker	No	Yes	No	Yes	2.9	69	90	7.0	7.0	7.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA

plotMDS(x1b)

message("here is the model spec:")

## here is the model spec:

dds <- DESeqDataSetFromMatrix(countData = x1b , colData = ss1b, design = ~ Metabolic_Syndrome )

## converting counts to integer mode

## Warning in DESeqDataSet(se, design = design, ignoreRank): some variables in
## design formula are characters, converting to factors

res <- DESeq(dds)

## estimating size factors

## estimating dispersions

## gene-wise dispersion estimates

## mean-dispersion relationship

## final dispersion estimates

## fitting model and testing

## -- replacing outliers and refitting for 220 genes
## -- DESeq argument 'minReplicatesForReplace' = 7 
## -- original counts are preserved in counts(dds)

## estimating dispersions

## fitting model and testing

z<- results(res)
vsd <- vst(dds, blind=FALSE)
zz <- cbind(as.data.frame(z),assay(vsd))
dge <- as.data.frame(zz[order(zz$pvalue),])

dge[1:20,1:6] %>%
  kbl(caption = "Top DEGs in bone between OA patients with and without metabolic syndrome.") %>%
  kable_paper("hover", full_width = F)

Top DEGs in bone between OA patients with and without metabolic syndrome.

	baseMean	log2FoldChange	lfcSE	stat	pvalue	padj
ENSG00000185269.12.NOTUM	21.84588	4.9570549	0.6003943	8.256332	0	0.00e+00
ENSG00000182600.9.SNORC	80.88169	4.4220506	0.6359907	6.953011	0	0.00e+00
ENSG00000167123.19.CERCAM	872.63471	2.2353965	0.3375271	6.622864	0	2.00e-07
ENSG00000138028.16.CGREF1	171.46614	2.5876088	0.3921460	6.598585	0	2.00e-07
ENSG00000142552.8.RCN3	954.08139	1.6072791	0.2467885	6.512779	0	3.00e-07
ENSG00000184471.8.C1QTNF8	27.80265	3.6632986	0.5911882	6.196501	0	1.70e-06
ENSG00000130600.19.H19	2387.16438	2.7108388	0.4584606	5.912915	0	8.30e-06
ENSG00000111199.12.TRPV4	163.35305	2.7838090	0.4741709	5.870898	0	9.40e-06
ENSG00000183010.17.PYCR1	297.80178	1.6239497	0.2790084	5.820433	0	1.13e-05
ENSG00000106415.13.GLCCI1	203.22265	-0.9088876	0.1570326	-5.787891	0	1.18e-05
ENSG00000139219.19.COL2A1	3398.50699	4.9972080	0.8647172	5.779008	0	1.18e-05
ENSG00000138316.11.ADAMTS14	115.57690	2.1902355	0.3820337	5.733094	0	1.42e-05
ENSG00000113739.11.STC2	44.58732	3.1362855	0.5483919	5.719058	0	1.43e-05
ENSG00000136457.10.CHAD	3017.47160	2.9434500	0.5195108	5.665811	0	1.77e-05
ENSG00000157766.19.ACAN	819.95444	3.4146378	0.6034953	5.658102	0	1.77e-05
ENSG00000137441.8.FGFBP2	596.89753	3.6004791	0.6416477	5.611302	0	2.18e-05
ENSG00000183196.10.CHST6	92.17133	3.0945377	0.5555569	5.570154	0	2.60e-05
ENSG00000204248.11.COL11A2	345.76660	1.8920244	0.3442054	5.496788	0	3.73e-05
ENSG00000281990.1.IGHV1.69.2	19.94618	-6.2076100	1.1364487	-5.462288	0	4.11e-05
ENSG00000141756.19.FKBP10	1435.20660	2.1650418	0.3970311	5.453079	0	4.11e-05

message("here is the model spec:")

## here is the model spec:

dds <- DESeqDataSetFromMatrix(countData = x1b , colData = ss1b, design = ~ Age + Sex + CRP + Metabolic_Syndrome )

## converting counts to integer mode

## Warning in DESeqDataSet(se, design = design, ignoreRank): some variables in
## design formula are characters, converting to factors

##   the design formula contains one or more numeric variables with integer values,
##   specifying a model with increasing fold change for higher values.
##   did you mean for this to be a factor? if so, first convert
##   this variable to a factor using the factor() function

##   the design formula contains one or more numeric variables that have mean or
##   standard deviation larger than 5 (an arbitrary threshold to trigger this message).
##   Including numeric variables with large mean can induce collinearity with the intercept.
##   Users should center and scale numeric variables in the design to improve GLM convergence.

res <- DESeq(dds)

## estimating size factors

## estimating dispersions

## gene-wise dispersion estimates

## mean-dispersion relationship

## final dispersion estimates

## fitting model and testing

## 1 rows did not converge in beta, labelled in mcols(object)$betaConv. Use larger maxit argument with nbinomWaldTest

z<- results(res)
vsd <- vst(dds, blind=FALSE)
zz <- cbind(as.data.frame(z),assay(vsd))
dge <- as.data.frame(zz[order(zz$pvalue),])

dge[1:20,1:6] %>%
  kbl(caption = "Top DEGs in bone between OA patients with and without metabolic syndrome, adjusted for age, sex and CRP.") %>%
  kable_paper("hover", full_width = F)

Top DEGs in bone between OA patients with and without metabolic syndrome, adjusted for age, sex and CRP.

	baseMean	log2FoldChange	lfcSE	stat	pvalue	padj
ENSG00000182600.9.SNORC	80.88169	4.230058	0.6478397	6.529482	0.0e+00	0.0000012
ENSG00000164106.8.SCRG1	226.95372	3.418468	0.5460676	6.260156	0.0e+00	0.0000034
ENSG00000186205.13.MTARC1	317.46675	-1.235527	0.2028667	-6.090336	0.0e+00	0.0000066
ENSG00000185269.12.NOTUM	21.84588	4.631073	0.8011530	5.780510	0.0e+00	0.0000330
ENSG00000171724.3.VAT1L	23.44098	2.034787	0.3672296	5.540913	0.0e+00	0.0001065
ENSG00000120885.22.CLU	12652.00431	3.397077	0.6201745	5.477614	0.0e+00	0.0001272
ENSG00000157766.19.ACAN	1526.34053	4.245406	0.7803311	5.440518	1.0e-07	0.0001343
ENSG00000113739.11.STC2	44.58732	3.653243	0.6766547	5.398977	1.0e-07	0.0001470
ENSG00000198892.7.SHISA4	70.95831	2.167296	0.4028927	5.379338	1.0e-07	0.0001470
ENSG00000176971.4.FIBIN	147.94606	3.109228	0.5850656	5.314325	1.0e-07	0.0001846
ENSG00000177106.16.EPS8L2	130.25154	2.131447	0.4020334	5.301666	1.0e-07	0.0001846
ENSG00000137441.8.FGFBP2	596.89753	3.549677	0.6814745	5.208818	2.0e-07	0.0002803
ENSG00000102313.9.ITIH6	38.89310	5.202700	1.0050249	5.176688	2.0e-07	0.0003075
ENSG00000130600.19.H19	2387.16438	3.035993	0.5916549	5.131358	3.0e-07	0.0003636
ENSG00000261857.7.MIA	115.03440	3.796352	0.7423445	5.114003	3.0e-07	0.0003721
ENSG00000154143.3.PANX3	13.86380	4.118535	0.8083235	5.095157	3.0e-07	0.0003854
ENSG00000260428.3.SCX	38.97017	1.833260	0.3620788	5.063153	4.0e-07	0.0004293
ENSG00000111199.12.TRPV4	163.35305	2.907016	0.5843122	4.975108	7.0e-07	0.0006412
ENSG00000237172.4.B3GNT9	151.84508	1.733289	0.3547988	4.885272	1.0e-06	0.0009621
ENSG00000188338.15.SLC38A3	26.63005	3.328527	0.6874607	4.841771	1.3e-06	0.0010543

dge1b <- dge

Now run a mitch analysis.

gnames <- sapply(strsplit(sub("\\."," ",sub("\\."," ",rownames(axx))) ," "),"[[",3)
gt <- data.frame(rownames(axx),gnames)

gs <- gmt_import("ReactomePathways_2023-09-01.gmt")

dge1b$gn <- sapply(strsplit( sub("\\.","_", ( sub("\\.","_",rownames(dge1b)) ) ), "_"),"[[",3)

m <- mitch_import(x=dge1b,DEtype="DESeq2",geneTable=gt)

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 18412

## Note: no. genes in output = 18383

## Note: estimated proportion of input genes in output = 0.998

mres1b <- mitch_calc(x=m,genesets=gs,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

head(mres1b$enrichment_result,20) %>%
  kbl(caption = "Top Reactomes for dge1b") %>%
  kable_paper("hover", full_width = F)

Top Reactomes for dge1b

	set	setSize	pANOVA	s.dist	p.adjustANOVA
1435	Unwinding of DNA	12	0.0000113	-0.7317965	0.0000835
535	Heme biosynthesis	13	0.0000060	-0.7246849	0.0000483
897	Polo-like kinase mediated events	16	0.0000006	-0.7194493	0.0000068
53	Activation of the pre-replicative complex	32	0.0000000	-0.7162280	0.0000000
375	Establishment of Sister Chromatid Cohesion	11	0.0000418	-0.7133484	0.0002650
450	G0 and Early G1	27	0.0000000	-0.6985142	0.0000000
373	Erythropoietin activates Phosphoinositide-3-kinase (PI3K)	11	0.0000680	-0.6935059	0.0004117
236	Crosslinking of collagen fibrils	17	0.0000010	0.6851023	0.0000101
1376	Transcription of E2F targets under negative control by DREAM complex	19	0.0000003	-0.6817286	0.0000033
211	Collagen biosynthesis and modifying enzymes	63	0.0000000	0.6810737	0.0000000
734	Mitotic Telophase/Cytokinesis	13	0.0000233	-0.6774926	0.0001559
310	Diseases associated with glycosaminoglycan metabolism	36	0.0000000	0.6670694	0.0000000
1377	Transcription of E2F targets under negative control by p107 (RBL1) and p130 (RBL2) in complex with HDAC1	16	0.0000046	-0.6615601	0.0000378
454	G1/S-Specific Transcription	29	0.0000000	-0.6537183	0.0000000
219	Condensation of Prometaphase Chromosomes	11	0.0001741	-0.6535934	0.0009609
264	DNA strand elongation	32	0.0000000	-0.6479654	0.0000000
670	MET activates PTK2 signaling	29	0.0000000	0.6458087	0.0000000
220	Condensation of Prophase Chromosomes	24	0.0000001	-0.6407166	0.0000008
36	Activation of ATR in response to replication stress	37	0.0000000	-0.6372256	0.0000000
145	CS/DS degradation	11	0.0002570	0.6364032	0.0013586

mitch_report(res=mres1b,outfile="mitch1boa_report.html",overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpQCsbbz/mitch1boa_report.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/34                             
## 2/34 [checklibraries]            
## 3/34                             
## 4/34 [peek]                      
## 5/34                             
## 6/34 [metrics]                   
## 7/34                             
## 8/34 [scatterplot]

## 9/34                             
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## 11/34                             
## 12/34 [input_geneset_metrics1]    
## 13/34                             
## 14/34 [input_geneset_metrics2]

## 15/34                             
## 16/34 [input_geneset_metrics3]

## 17/34                             
## 18/34 [echart1d]                  
## 19/34 [echart2d]                  
## 20/34                             
## 21/34 [heatmap]                   
## 22/34                             
## 23/34 [effectsize]                
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## 25/34 [results_table]             
## 26/34                             
## 27/34 [results_table_complete]    
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## 29/34 [detailed_geneset_reports1d]

## 30/34                             
## 31/34 [detailed_geneset_reports2d]
## 32/34                             
## 33/34 [session_info]              
## 34/34

## output file: /mnt/data/mdz/projects/shoulder/shoulder-instability-osteroarthritis/mitch.knit.md

## /home/mdz/anaconda3/bin/pandoc +RTS -K512m -RTS /mnt/data/mdz/projects/shoulder/shoulder-instability-osteroarthritis/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpQCsbbz/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --self-contained --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpQCsbbz/rmarkdown-str38ec93250a3b6e.html

## 
## Output created: /tmp/RtmpQCsbbz/mitch_report.html

## [1] TRUE

The effect of metabolic syndrome in cuff arthropathy - consider all tissues

Need to:

• select cuff arthropathy samples only

• look at the effect of metabolic syndrome in OA (ss1).

• consider tissues as “batches” to correct for.

• Unfortunately it isn’t possible to correct for participant “batches” at the same time.

ss1 <- subset(ss,Cuff_Arthropathy=="Yes")

message("Metabolic syndrome classification")

## Metabolic syndrome classification

ss1$Metabolic_Syndrome

##  [1] "No"  "No"  "No"  "No"  "Yes" "Yes" "Yes" "Yes" "No"  "Yes" "Yes" "Yes"
## [13] "No"  "No"  "No"

message("Age data")

## Age data

ss1$Age

##  [1] 80 80 80 76 69 69 69 71 79 74 74 74 72 72 72

message("Sex data")

## Sex data

ss1$Sex

##  [1] "F" "F" "F" "M" "F" "F" "F" "M" "F" "F" "F" "F" "M" "M" "M"

x1 <- axx[,colnames(axx) %in% rownames(ss1)]
message("count matrix dimensions before filtering out low genes")

## count matrix dimensions before filtering out low genes

dim(x1)

## [1] 60651    15

x1 <- x1[which(rowMeans(x1)>=10),]
message("count matrix dimensions after filtering out low genes")

## count matrix dimensions after filtering out low genes

dim(x1)

## [1] 17836    15

x1 <- x1[,order(colnames(x1))]
ss1 <- ss1[order(rownames(ss1)),]

ss1 %>%
  kbl(caption = "sample sheet") %>%
  kable_paper("hover", full_width = F)

sample sheet

	Participant_ID	Case	Redcap_ID	Tissue	fastq	pvt.pub	Age	Sex	Primary_OA	Cuff_Arthropathy	Prosthesis	Affected_Side	Height_cm	Weight_kg	BMI	ASA	Smoking	Diabetes	Hypercholesterolaemia	Hypertension	Thyroid	CRP	Creat	eGFR	Urea	Fast_Glucose	hba1c	Metabolic_Syndrome	Tendon_integrity_2_years_post.op	ASES_2_years_post.op_Pain	ASES_2_years_post.op_ADL	ASES_2_years_post.op_Total	Oxford_Baseline	Oxford_3_month	Oxford_12_month	Oxford_24_month	QuickDASH_	QuickDASH_3_month	QuickDASH_12_month	QuickDASH_24_month	EQ.5D.3L_Baseline	EQ.5D.3L_3_month	EQ.5D.3L_12_month	EQ.5D.3L_24_month	EQVAS_Baseline	EQVAS_3_month	EQVAS_12_month	EQVAS_24_month
10B_S21	AD-CAB_4010	OA	90	bone	10B_S21_L001_R1_001.fastq.gz	pvt	80	F	No	Yes	Reverse	Left	161	72	28	2	Never_smoker	No	Yes	No	Yes	11.2	54	86	8.5	7.3	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
10C_S35	AD-CAB_4010	OA	90	capsule	10C_S35_L001_R1_001.fastq.gz	pvt	80	F	No	Yes	Reverse	Left	161	72	28	2	Never_smoker	No	Yes	No	Yes	11.2	54	86	8.5	7.3	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
10S_S49	AD-CAB_4010	OA	90	synovium	10S_S49_L001_R1_001.fastq.gz	pvt	80	F	No	Yes	Reverse	Left	161	72	28	2	Never_smoker	No	Yes	No	Yes	11.2	54	86	8.5	7.3	5.6	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
11C_S36	AD-CAB_4011	OA	87	capsule	11C_S36_L001_R1_001.fastq.gz	pub	76	M	No	Yes	Reverse	Right	180	92	28	2	Never_smoker	No	Yes	Yes	No	4.0	75	85	7.0	6.0	6.0	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
13B_S24	AD-CAB_4013	OA	89	bone	13B_S24_L001_R1_001.fastq.gz	pvt	69	F	No	Yes	Reverse	Left	170	89	31	2	Never_smoker	No	Yes	Yes	No	2.9	81	85	5.1	5.4	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
13C_S38	AD-CAB_4013	OA	89	capsule	13C_S38_L001_R1_001.fastq.gz	pvt	69	F	No	Yes	Reverse	Left	170	89	31	2	Never_smoker	No	Yes	Yes	No	2.9	81	85	5.1	5.4	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
13S_S52	AD-CAB_4013	OA	89	synovium	13S_S52_L001_R1_001.fastq.gz	pvt	69	F	No	Yes	Reverse	Left	170	89	31	2	Never_smoker	No	Yes	Yes	No	2.9	81	85	5.1	5.4	5.9	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
14C_S39	AD-CAB_4014	OA	92	capsule	14C_S39_L001_R1_001.fastq.gz	pvt	71	M	No	Yes	Reverse	Right	170	99	34	2	Ever_smoker	No	Yes	No	Yes	2.9	69	90	7.0	7.0	7.1	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
17C_S42	AD-CAB_4017	OA	96	capsule	17C_S42_L001_R1_001.fastq.gz	pvt	79	F	No	Yes	Reverse	Right	155	75	31	2	Never_smoker	No	No	No	No	9.2	71	70	4.5	5.5	5.1	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4003.43B	AD-CAB_4003	OA	81	bone	4003-43B_R1_001.fastq.gz	pvt	74	F	No	Yes	Reverse	Right	153	87	37	2	Ever_smoker	No	Yes	Yes	No	6.9	77	66	5.0	5.4	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4003.43C	AD-CAB_4003	OA	81	capsule	4003-43C_R1_001.fastq.gz	pvt	74	F	No	Yes	Reverse	Right	153	87	37	2	Ever_smoker	No	Yes	Yes	No	6.9	77	66	5.0	5.4	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
4003.43S	AD-CAB_4003	OA	81	synovium	4003-43S_R1_001.fastq.gz	pvt	74	F	No	Yes	Reverse	Right	153	87	37	2	Ever_smoker	No	Yes	Yes	No	6.9	77	66	5.0	5.4	5.4	Yes	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
9B_S20	AD-CAB_4009	OA	88	bone	9B_S20_L001_R1_001.fastq.gz	pvt	72	M	No	Yes	Reverse	Right	167	80	29	3	Ever_smoker	No	Yes	Yes	No	2.9	107	59	6.7	5.8	5.5	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
9C_S34	AD-CAB_4009	OA	88	capsule	9C_S34_L001_R1_001.fastq.gz	pvt	72	M	No	Yes	Reverse	Right	167	80	29	3	Ever_smoker	No	Yes	Yes	No	2.9	107	59	6.7	5.8	5.5	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
9S_S48	AD-CAB_4009	OA	88	synovium	9S_S48_L001_R1_001.fastq.gz	pvt	72	M	No	Yes	Reverse	Right	167	80	29	3	Ever_smoker	No	Yes	Yes	No	2.9	107	59	6.7	5.8	5.5	No	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA

plotMDS(x1)

message("here is the model spec:")

## here is the model spec:

dds <- DESeqDataSetFromMatrix(countData = x1 , colData = ss1, design = ~ Tissue + Metabolic_Syndrome )

## converting counts to integer mode

## Warning in DESeqDataSet(se, design = design, ignoreRank): some variables in
## design formula are characters, converting to factors

res <- DESeq(dds)

## estimating size factors

## estimating dispersions

## gene-wise dispersion estimates

## mean-dispersion relationship

## final dispersion estimates

## fitting model and testing

z<- results(res)
vsd <- vst(dds, blind=FALSE)
zz <- cbind(as.data.frame(z),assay(vsd))
dge <- as.data.frame(zz[order(zz$pvalue),])

dge[1:20,1:6] %>%
  kbl(caption = "Top DEGs that are altered in all tissues by metabolic syndrome.") %>%
  kable_paper("hover", full_width = F)

Top DEGs that are altered in all tissues by metabolic syndrome.

	baseMean	log2FoldChange	lfcSE	stat	pvalue	padj
ENSG00000171798.18.KNDC1	17.52212	-3.274925	0.6181115	-5.298276	0.0000001	0.0010439
ENSG00000071859.15.FAM50A	2743.93745	-2.711501	0.5119569	-5.296346	0.0000001	0.0010439
ENSG00000269900.3.RMRP	74.42722	-7.205598	1.4042967	-5.131108	0.0000003	0.0016968
ENSG00000153266.13.FEZF2	33.57803	-3.203489	0.6874521	-4.659945	0.0000032	0.0139739
ENSG00000156076.10.WIF1	272.49627	-4.115397	0.8988475	-4.578526	0.0000047	0.0165503
ENSG00000129988.6.LBP	97.13172	-2.881010	0.6374514	-4.519576	0.0000062	0.0182503
ENSG00000162188.6.GNG3	20.13093	-4.216226	0.9603866	-4.390135	0.0000113	0.0246764
ENSG00000138135.7.CH25H	19.94769	-2.647419	0.6049496	-4.376263	0.0000121	0.0246764
ENSG00000174738.13.NR1D2	260.86392	1.394920	0.3193857	4.367508	0.0000126	0.0246764
ENSG00000101282.9.RSPO4	17.54382	-3.360214	0.7922278	-4.241475	0.0000222	0.0392417
ENSG00000196656.7.AC004057.1	353.96613	1.831635	0.4522281	4.050245	0.0000512	0.0821972
ENSG00000197728.11.RPS26	659.66768	1.162675	0.2946911	3.945404	0.0000797	0.1167178
ENSG00000256654.4.AC005906.2	29.77701	2.300732	0.5858120	3.927423	0.0000859	0.1167178
ENSG00000267314.1.AC104532.1	7.05486	5.307702	1.3632342	3.893463	0.0000988	0.1247431
ENSG00000212864.3.RNF208	22.84818	-2.221922	0.5771325	-3.849934	0.0001181	0.1336789
ENSG00000125740.14.FOSB	2030.19009	-3.173144	0.8276443	-3.833946	0.0001261	0.1336789
ENSG00000123977.10.DAW1	31.07425	2.507415	0.6548258	3.829133	0.0001286	0.1336789
ENSG00000196091.15.MYBPC1	16.46819	3.601125	0.9641224	3.735133	0.0001876	0.1841973
ENSG00000214940.8.NPIPA8	19.30323	4.324186	1.1630242	3.718053	0.0002008	0.1867315
ENSG00000104722.14.NEFM	39.35629	-2.917603	0.7986736	-3.653061	0.0002591	0.2224579

message("here is the model spec:")

## here is the model spec:

dds <- DESeqDataSetFromMatrix(countData = x1 , colData = ss1, design = ~ Age + Sex + CRP + Metabolic_Syndrome )

## converting counts to integer mode

## Warning in DESeqDataSet(se, design = design, ignoreRank): some variables in
## design formula are characters, converting to factors

##   the design formula contains one or more numeric variables with integer values,
##   specifying a model with increasing fold change for higher values.
##   did you mean for this to be a factor? if so, first convert
##   this variable to a factor using the factor() function

##   the design formula contains one or more numeric variables that have mean or
##   standard deviation larger than 5 (an arbitrary threshold to trigger this message).
##   Including numeric variables with large mean can induce collinearity with the intercept.
##   Users should center and scale numeric variables in the design to improve GLM convergence.

res <- DESeq(dds)

## estimating size factors

## estimating dispersions

## gene-wise dispersion estimates

## mean-dispersion relationship

## -- note: fitType='parametric', but the dispersion trend was not well captured by the
##    function: y = a/x + b, and a local regression fit was automatically substituted.
##    specify fitType='local' or 'mean' to avoid this message next time.

## final dispersion estimates

## fitting model and testing

z<- results(res)
vsd <- vst(dds, blind=FALSE)

## -- note: fitType='parametric', but the dispersion trend was not well captured by the
##    function: y = a/x + b, and a local regression fit was automatically substituted.
##    specify fitType='local' or 'mean' to avoid this message next time.

zz <- cbind(as.data.frame(z),assay(vsd))
dge <- as.data.frame(zz[order(zz$pvalue),])

dge[1:20,1:6] %>%
  kbl(caption = "Top DEGs in bone between cuff arthropathy patients with and without metabolic syndrome, adjusted for age, sex and CRP.") %>%
  kable_paper("hover", full_width = F)

Top DEGs in bone between cuff arthropathy patients with and without metabolic syndrome, adjusted for age, sex and CRP.

	baseMean	log2FoldChange	lfcSE	stat	pvalue	padj
ENSG00000198959.12.TGM2	315.86349	-3.3507315	0.6414867	-5.223384	0.0000002	0.0025472
ENSG00000155980.13.KIF5A	129.07520	-4.2775322	0.9604122	-4.453851	0.0000084	0.0611450
ENSG00000160469.17.BRSK1	50.46854	-3.3693750	0.7810636	-4.313829	0.0000160	0.0775459
ENSG00000110536.14.PTPMT1	167.27421	1.0628621	0.2731142	3.891640	0.0000996	0.2995526
ENSG00000163032.12.VSNL1	44.06568	-4.1565301	1.0705245	-3.882704	0.0001033	0.2995526
ENSG00000123240.17.OPTN	590.92539	1.2887951	0.3398298	3.792472	0.0001492	0.3016345
ENSG00000144118.14.RALB	546.14797	1.3212304	0.3504421	3.770182	0.0001631	0.3016345
ENSG00000069020.18.MAST4	122.05000	-1.9906119	0.5286900	-3.765178	0.0001664	0.3016345
ENSG00000146021.15.KLHL3	100.88844	-2.2875423	0.6158306	-3.714564	0.0002036	0.3018224
ENSG00000123200.17.ZC3H13	498.60552	-0.7312717	0.1971671	-3.708893	0.0002082	0.3018224
ENSG00000006451.8.RALA	186.36820	1.4128225	0.3868378	3.652235	0.0002600	0.3216342
ENSG00000168209.6.DDIT4	1304.45036	-2.6283417	0.7224367	-3.638162	0.0002746	0.3216342
ENSG00000066697.15.MSANTD3	137.19776	1.8272517	0.5052075	3.616834	0.0002982	0.3216342
ENSG00000262879.6.AC005670.3	170.63779	-1.1064848	0.3068179	-3.606324	0.0003106	0.3216342
ENSG00000187957.8.DNER	45.15783	-5.1965309	1.5368155	-3.381363	0.0007213	0.6513570
ENSG00000167775.11.CD320	174.06002	-2.4803583	0.7388680	-3.356971	0.0007880	0.6513570
ENSG00000136997.21.MYC	358.06883	-1.8769850	0.5594960	-3.354779	0.0007943	0.6513570
ENSG00000196656.7.AC004057.1	353.96613	2.9485435	0.8907317	3.310249	0.0009321	0.6513570
ENSG00000157601.15.MX1	259.68722	1.6875061	0.5120564	3.295547	0.0009823	0.6513570
ENSG00000185115.6.NSMCE3	98.35523	1.0260843	0.3117454	3.291418	0.0009968	0.6513570

dge1 <- dge

Now run a mitch analysis.

gnames <- sapply(strsplit(sub("\\."," ",sub("\\."," ",rownames(axx))) ," "),"[[",3)
gt <- data.frame(rownames(axx),gnames)

gs <- gmt_import("ReactomePathways_2023-09-01.gmt")

dge1$gn <- sapply(strsplit( sub("\\.","_", ( sub("\\.","_",rownames(dge1)) ) ), "_"),"[[",3)

m <- mitch_import(x=dge1,DEtype="DESeq2",geneTable=gt)

## The input is a single dataframe; one contrast only. Converting
##         it to a list for you.

## Note: Mean no. genes in input = 17836

## Note: no. genes in output = 17810

## Note: estimated proportion of input genes in output = 0.999

mres1 <- mitch_calc(x=m,genesets=gs,cores=16,priority="effect")

## Note: Enrichments with large effect sizes may not be
##             statistically significant.

head(mres1$enrichment_result,20) %>%
  kbl(caption = "Top Reactomes for dge1b") %>%
  kable_paper("hover", full_width = F)

Top Reactomes for dge1b

	set	setSize	pANOVA	s.dist	p.adjustANOVA
413	Folding of actin by CCT/TriC	10	0.0002124	0.6763258	0.0011235
638	LGI-ADAM interactions	11	0.0003973	-0.6166894	0.0019000
375	Establishment of Sister Chromatid Cohesion	11	0.0004628	0.6096410	0.0021652
107	BBSome-mediated cargo-targeting to cilium	21	0.0000027	0.5914972	0.0000198
1085	Regulation of ornithine decarboxylase (ODC)	48	0.0000000	0.5786229	0.0000000
1138	SLBP Dependent Processing of Replication-Dependent Histone Pre-mRNAs	11	0.0009390	0.5760130	0.0040626
722	Mitochondrial translation initiation	88	0.0000000	0.5668981	0.0000000
723	Mitochondrial translation termination	88	0.0000000	0.5656311	0.0000000
720	Mitochondrial translation	94	0.0000000	0.5653863	0.0000000
210	Cohesin Loading onto Chromatin	10	0.0020277	0.5635730	0.0079255
248	Cytosolic tRNA aminoacylation	24	0.0000019	0.5618230	0.0000142
1105	Response to metal ions	11	0.0012710	-0.5610887	0.0052998
721	Mitochondrial translation elongation	88	0.0000000	0.5556614	0.0000000
1446	Vif-mediated degradation of APOBEC3G	52	0.0000000	0.5547684	0.0000000
1071	Regulation of activated PAK-2p34 by proteasome mediated degradation	48	0.0000000	0.5514113	0.0000000
1454	Vpu mediated degradation of CD4	50	0.0000000	0.5481734	0.0000000
470	GSK3B and BTRC:CUL1-mediated-degradation of NFE2L2	52	0.0000000	0.5452515	0.0000000
414	Formation of ATP by chemiosmotic coupling	16	0.0001622	0.5445515	0.0008929
1139	SLBP independent Processing of Histone Pre-mRNAs	10	0.0032467	0.5375056	0.0120006
1034	Regulation of Apoptosis	51	0.0000000	0.5353320	0.0000000

mitch_report(res=mres1,outfile="mitch1_report.html",overwrite=TRUE)

## Note: overwriting existing report

## Dataset saved as " /tmp/RtmpQCsbbz/mitch1_report.rds ".

## 
## 
## processing file: mitch.Rmd

## 1/34                             
## 2/34 [checklibraries]            
## 3/34                             
## 4/34 [peek]                      
## 5/34                             
## 6/34 [metrics]                   
## 7/34                             
## 8/34 [scatterplot]

## 9/34                             
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## 11/34                             
## 12/34 [input_geneset_metrics1]    
## 13/34                             
## 14/34 [input_geneset_metrics2]

## 15/34                             
## 16/34 [input_geneset_metrics3]

## 17/34                             
## 18/34 [echart1d]                  
## 19/34 [echart2d]                  
## 20/34                             
## 21/34 [heatmap]                   
## 22/34                             
## 23/34 [effectsize]                
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## 25/34 [results_table]             
## 26/34                             
## 27/34 [results_table_complete]    
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## 29/34 [detailed_geneset_reports1d]

## 30/34                             
## 31/34 [detailed_geneset_reports2d]
## 32/34                             
## 33/34 [session_info]              
## 34/34

## output file: /mnt/data/mdz/projects/shoulder/shoulder-instability-osteroarthritis/mitch.knit.md

## /home/mdz/anaconda3/bin/pandoc +RTS -K512m -RTS /mnt/data/mdz/projects/shoulder/shoulder-instability-osteroarthritis/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpQCsbbz/mitch_report.html --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/pagebreak.lua --lua-filter /usr/local/lib/R/site-library/rmarkdown/rmarkdown/lua/latex-div.lua --self-contained --variable bs3=TRUE --section-divs --template /usr/local/lib/R/site-library/rmarkdown/rmd/h/default.html --no-highlight --variable highlightjs=1 --variable theme=bootstrap --mathjax --variable 'mathjax-url=https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML' --include-in-header /tmp/RtmpQCsbbz/rmarkdown-str38ec936a02d103.html

## 
## Output created: /tmp/RtmpQCsbbz/mitch_report.html

## [1] TRUE

The effect of metabolic syndrome in rotator cuff

Need to:

• Select rotator cuff

• look at the effect of metabolic syndrome.

ss2 <- subset(ss,Case=="RC")

ss2c <- subset(ss2,Tissue=="capsule")

message("Metabolic syndrome classification")

## Metabolic syndrome classification

ss2c$Metabolic_Syndrome

##  [1] "Yes" "No"  "No"  "No"  "Yes" "Yes" "Yes" "No"  "No"  "No"  "Yes" "No" 
## [13] "No"  "No"  NA    "No"  "No"  "Yes" "Yes" "No"  "No"  NA    "No"  "No" 
## [25] "No"  "No"

message("Age data")

## Age data

ss2c$Age

##  [1] 67 58 50 72 68 70 66 68 60 72 45 58 61 46 39 58 52 62 59 56 68 59 65 63 70
## [26] 68

message("Sex data")

## Sex data

ss2c$Sex

##  [1] "M" "M" "M" "M" "F" "M" "M" "M" "M" "M" "F" "M" "M" "M" "F" "M" "F" "F" "M"
## [20] "M" "M" "F" "M" "F" "M" "M"

x2c <- axx[,colnames(axx) %in% rownames(ss2c)]
message("count matrix dimensions before filtering out low genes")

## count matrix dimensions before filtering out low genes

dim(x2c)

## [1] 60651    26

x2c <- x2c[which(rowMeans(x2c)>=10),]
message("count matrix dimensions after filtering out low genes")

## count matrix dimensions after filtering out low genes

dim(x2c)

## [1] 16169    26

x2c <- x2c[,order(colnames(x2c))]
ss2c <- ss2c[order(rownames(ss2c)),]

ss2c <- subset(ss2c,Metabolic_Syndrome=="No" | Metabolic_Syndrome=="Yes")
x2c <- x2c[,colnames(x2c) %in% rownames(ss2c)]

ss2c %>%
  kbl(caption = "sample sheet") %>%
  kable_paper("hover", full_width = F)

sample sheet

	Participant_ID	Case	Redcap_ID	Tissue	fastq	pvt.pub	Age	Sex	Primary_OA	Cuff_Arthropathy	Prosthesis	Affected_Side	Height_cm	Weight_kg	BMI	ASA	Smoking	Diabetes	Hypercholesterolaemia	Hypertension	Thyroid	CRP	Creat	eGFR	Urea	Fast_Glucose	hba1c	Metabolic_Syndrome	Tendon_integrity_2_years_post.op	ASES_2_years_post.op_Pain	ASES_2_years_post.op_ADL	ASES_2_years_post.op_Total	Oxford_Baseline	Oxford_3_month	Oxford_12_month	Oxford_24_month	QuickDASH_	QuickDASH_3_month	QuickDASH_12_month	QuickDASH_24_month	EQ.5D.3L_Baseline	EQ.5D.3L_3_month	EQ.5D.3L_12_month	EQ.5D.3L_24_month	EQVAS_Baseline	EQVAS_3_month	EQVAS_12_month	EQVAS_24_month
1.1_S41	AD-CAB_3001	RC	53	capsule	1-1_S41_L001_R1_001.fastq.gz	NA	67	M	NA	NA	NA	Left	177.80	120	37.90	2	Ever_smoker	No	Yes	Yes	No	2.9	83	84	7.0	5.2	5.6	Yes	Torn	NA	NA	NA	25	41	46	NA	38.6	13.6	13.6	NA	11222	11123	21222	NA	90	50	60	NA
10.1_S50	AD-CAB_3010	RC	62	capsule	10-1_S50_L001_R1_001.fastq.gz	NA	58	M	NA	NA	NA	Left	179.00	98	30.00	2	Never_smoker	No	No	No	Yes	2.9	82	90	5.6	4.9	5.1	No	Intact	45	17	62	21	45	43	44	45.5	4.5	11.4	20.5	11221	11111	11121	11221	70	70	75	85
11.1_S51	AD-CAB_3011	RC	63	capsule	11-1_S51_L001_R1_001.fastq.gz	NA	50	M	NA	NA	NA	Right	180.00	82	25.00	1	Never_smoker	No	Yes	No	No	2.9	99	76	6.7	5.7	6.0	No	Intact	35	18	53	18	38	44	46	61.4	31.8	6.8	20.5	11221	11222	11111	11121	75	83	75	78
12.1_S52	AD-CAB_3012	RC	64	capsule	12-1_S52_L001_R1_001.fastq.gz	NA	72	M	NA	NA	NA	Left	173.00	87	29.00	3	Never_smoker	Yes	Yes	Yes	No	2.9	108	59	4.8	6.1	6.6	No	NA	50	48	98	29	32	48	42	68.2	0.0	4.5	18.2	12221	11111	11111	11111	70	90	80	90
13.1_S53	AD-CAB_3013	RC	65	capsule	13-1_S53_L001_R1_001.fastq.gz	NA	68	F	NA	NA	NA	Right	161.00	104	40.00	3	Never_smoker	Yes	No	Yes	No	6.3	64	86	6.8	9.2	7.1	Yes	NA	45	45	90	19	34	48	46	75.0	50.0	6.8	2.3	11222	11221	22221	21231	89	78	50	50
14.1_S54	AD-CAB_3014	RC	66	capsule	14-1_S54_L001_R1_001.fastq.gz	NA	70	M	NA	NA	NA	Left	1.77	100	32.00	3	Ever_smoker	No	Yes	Yes	No	2.9	86	79	7.1	6.3	5.8	Yes	Intact	50	45	95	27	43	47	47	50.0	9.1	6.8	9.1	12221	11111	11111	11111	90	90	88	85
15.1_S55	AD-CAB_3015	RC	69	capsule	15-1_S55_L001_R1_001.fastq.gz	NA	66	M	NA	NA	NA	Left	175.00	95	31.00	3	Never_smoker	No	Yes	Yes	No	2.9	53	90	4.1	5.5	5.2	Yes	Intact	50	47	97	25	NA	NA	48	40.9	NA	NA	13.6	11121	NA	NA	11121	78	NA	NA	93
16.1_S56	AD-CAB_3016	RC	71	capsule	16-1_S56_L001_R1_001.fastq.gz	NA	68	M	NA	NA	NA	Left	180.00	88	27.00	1	Ever_smoker	Yes	No	Yes	No	2.9	73	90	4.7	7.3	8.3	No	Torn	40	42	82	24	27	45	43	43.2	38.6	6.8	11.4	11122	11222	11112	11121	70	60	50	80
17.1_S57	AD-CAB_3017	RC	70	capsule	17-1_S57_L001_R1_001.fastq.gz	NA	60	M	NA	NA	NA	Left	166.00	80	29.00	2	Ever_smoker	No	No	No	No	2.9	119	57	7.2	NA	5.7	No	Torn	NA	NA	NA	13	40	NA	NA	93.2	38.6	NA	NA	12221	21211	NA	NA	70	60	NA	NA
18.1_S58	AD-CAB_3018	RC	72	capsule	18-1_S58_L001_R1_001.fastq.gz	NA	72	M	NA	NA	NA	Right	170.00	85	29.00	2	Ever_smoker	No	Yes	Yes	No	3.2	82	82	6.4	5.5	5.5	No	Intact	50	50	100	36	37	48	48	31.8	13.6	9.1	0.0	11122	11112	11111	11111	90	82	92	90
19.1_S59	AD-CAB_3019	RC	73	capsule	19-1_S59_L001_R1_001.fastq.gz	NA	45	F	NA	NA	NA	Right	163.00	98	36.90	2	Never_smoker	No	Yes	Yes	No	4.3	70	57	4.6	4.7	5.7	Yes	Intact	50	35	85	32	28	45	47	36.4	38.6	18.2	13.6	11221	11221	11121	11121	50	58	45	34
2.1_S42	AD-CAB_3002	RC	54	capsule	2-1_S42_L001_R1_001.fastq.gz	NA	58	M	NA	NA	NA	Right	179.00	79	25.00	1	Never_smoker	No	No	No	No	0.7	70	90	6.9	5.4	5.3	No	Torn	NA	NA	NA	33	NA	48	NA	29.5	NA	0.0	NA	11111	NA	11111	NA	90	NA	90	NA
20.1_S60	AD-CAB_3020	RC	67	capsule	20-1_S60_L001_R1_001.fastq.gz	NA	61	M	NA	NA	NA	Right	180.00	92	29.00	1	Ever_smoker	No	No	No	No	2.9	78	57	3.9	5.5	5.6	No	Intact	50	40	90	30	34	36	44	50.0	34.1	31.8	0.0	12321	12321	12211	12211	77	40	70	70
21.1_S61	AD-CAB_3021	RC	68	capsule	21-1_S61_L001_R1_001.fastq.gz	NA	46	M	NA	NA	NA	Right	180.00	88	27.20	2	Never_smoker	No	Yes	No	No	2.9	77	57	5.9	5.9	5.3	No	Torn	NA	NA	NA	29	44	43	NA	45.5	20.5	11.4	NA	NA	11111	11121	NA	NA	80	65	NA
23.1_S63	AD-CAB_3023	RC	75	capsule	23-1_S63_L001_R1_001.fastq.gz	NA	58	M	NA	NA	NA	Right	179.00	81	25.00	2	Ever_smoker	No	Yes	No	No	2.9	75	57	5.7	5.4	5.7	No	Intact	50	40	90	42	43	48	48	15.9	15.9	0.0	2.3	11211	11121	11111	11111	85	85	90	85
24.1_S64	AD-CAB_3024	RC	76	capsule	24-1_S64_L001_R1_001.fastq.gz	NA	52	F	NA	NA	NA	Right	153.00	70	28.00	2	Never_smoker	No	Yes	Yes	Yes	3.0	64	57	7.8	5.6	6.4	No	NA	NA	NA	NA	26	23	NA	NA	56.8	45.5	NA	NA	12222	12221	NA	NA	30	60	NA	NA
25.1_S65	AD-CAB_3025	RC	77	capsule	25-1_S65_L001_R1_001.fastq.gz	NA	62	F	NA	NA	NA	Left	157.00	95	38.50	2	Never_smoker	No	Yes	Yes	No	12.0	72	57	6.6	6.2	5.7	Yes	Intact	45	43	88	26	36	38	41	59.1	29.5	31.8	18.2	12231	11221	11221	11121	82	80	60	80
26.1_S66	AD-CAB_3026	RC	79	capsule	26-1_S66_L001_R1_001.fastq.gz	NA	59	M	NA	NA	NA	Right	176.00	104	33.70	2	Ever_smoker	No	Yes	Yes	No	2.9	62	57	4.2	3.6	5.3	Yes	NA	NA	NA	NA	30	42	44	NA	38.6	25.0	22.7	NA	12222	11222	11221	NA	70	90	90	NA
3.1_S43	AD-CAB_3003	RC	55	capsule	3-1_S43_L001_R1_001.fastq.gz	NA	56	M	NA	NA	NA	Left	179.00	85	26.52	1	Never_smoker	No	Yes	NA	No	2.9	72	90	4.3	5.2	5.4	No	Intact	50	50	100	38	38	44	48	29.5	27.3	9.1	0.0	11221	11121	11111	22222	80	70	80	60
4.1_S44	AD-CAB_3004	RC	56	capsule	4-1_S44_L001_R1_001.fastq.gz	NA	68	M	NA	NA	NA	Right	185.00	95	28.00	2	Ever_smoker	No	Yes	Yes	No	3.6	91	74	7.8	6.7	5.7	No	Intact	45	50	95	24	41	46	48	NA	18.2	13.6	0.0	11232	11121	11121	11111	NA	80	60	52
6.1_S46	AD-CAB_3006	RC	58	capsule	6-1_S46_L001_R1_001.fastq.gz	NA	65	M	NA	NA	NA	Left	172.00	78	26.00	1	Never_smoker	No	No	No	No	2.9	77	90	5.6	4.8	5.4	No	Torn	NA	NA	NA	35	31	37	NA	34.1	36.4	27.3	NA	12221	11221	11111	NA	82	40	80	NA
7.1_S47	AD-CAB_3007	RC	59	capsule	7-1_S47_L001_R1_001.fastq.gz	NA	63	F	NA	NA	NA	Right	163.00	57	21.50	1	Ever_smoker	No	No	No	No	2.9	53	90	29.0	NA	5.3	No	Intact	50	50	100	37	38	46	48	36.4	18.2	11.4	2.3	11122	11111	11111	11111	93	97	100	100
8.1_S48	AD-CAB_3008	RC	60	capsule	8-1_S48_L001_R1_001.fastq.gz	NA	70	M	NA	NA	NA	Left	167.00	71	25.50	2	Never_smoker	No	Yes	Yes	No	2.9	87	77	7.3	5.5	5.4	No	Intact	NA	NA	NA	24	25	47	NA	54.5	54.5	11.4	NA	22221	22221	11111	NA	90	90	92	NA
9.1_S49	AD-CAB_3009	RC	61	capsule	9-1_S49_L001_R1_001.fastq.gz	NA	68	M	NA	NA	NA	Right	182.00	83	25.10	2	Ever_smoker	No	No	No	No	2.9	79	88	7.5	5.8	5.8	No	Intact	50	50	100	35	41	43	46	52.3	11.4	4.5	2.3	11211	11121	11111	11111	85	96	90	90

plotMDS(x2c)

message("here is the model spec:")

## here is the model spec:

dds <- DESeqDataSetFromMatrix(countData = x2c , colData = ss2c, design = ~ Age + Sex + Metabolic_Syndrome )

## converting counts to integer mode

## Warning in DESeqDataSet(se, design = design, ignoreRank): some variables in
## design formula are characters, converting to factors

##   the design formula contains one or more numeric variables with integer values,
##   specifying a model with increasing fold change for higher values.
##   did you mean for this to be a factor? if so, first convert
##   this variable to a factor using the factor() function

##   the design formula contains one or more numeric variables that have mean or
##   standard deviation larger than 5 (an arbitrary threshold to trigger this message).
##   Including numeric variables with large mean can induce collinearity with the intercept.
##   Users should center and scale numeric variables in the design to improve GLM convergence.

res <- DESeq(dds)

## estimating size factors

## estimating dispersions

## gene-wise dispersion estimates

## mean-dispersion relationship

## final dispersion estimates

## fitting model and testing

z<- results(res)
vsd <- vst(dds, blind=FALSE)
zz <- cbind(as.data.frame(z),assay(vsd))
dge <- as.data.frame(zz[order(zz$pvalue),])

dge[1:20,1:6] %>%
  kbl(caption = "Top DEGs in capsule between RC patients with and without metabolic syndrome.") %>%
  kable_paper("hover", full_width = F)

Top DEGs in capsule between RC patients with and without metabolic syndrome.

	baseMean	log2FoldChange	lfcSE	stat	pvalue	padj
ENSG00000203812.2.H2AC18	15.61564	-3.9010306	0.9263541	-4.211166	0.0000254	0.4104532
ENSG00000197614.11.MFAP5	1259.04222	-2.5068148	0.6332143	-3.958872	0.0000753	0.6083095
ENSG00000198121.13.LPAR1	765.32020	-0.6662140	0.1745208	-3.817389	0.0001349	0.6255534
ENSG00000287286.1.AC024560.5	13.29192	-3.3780136	0.9145029	-3.693825	0.0002209	0.6255534
ENSG00000145113.22.MUC4	14.16622	-1.9818044	0.5404158	-3.667184	0.0002452	0.6255534
ENSG00000135916.16.ITM2C	307.48864	-1.5101725	0.4135695	-3.651557	0.0002607	0.6255534
ENSG00000162545.6.CAMK2N1	75.26906	-1.6038568	0.4404365	-3.641516	0.0002710	0.6255534
ENSG00000267339.7.LINC00906	10.54983	-2.3568631	0.6633982	-3.552712	0.0003813	0.6910479
ENSG00000218336.9.TENM3	19.03004	1.3566231	0.3821275	3.550185	0.0003850	0.6910479
ENSG00000148357.16.HMCN2	551.37442	-1.7044676	0.4899756	-3.478679	0.0005039	0.8140891
ENSG00000133063.16.CHIT1	19.87184	2.6044350	0.7666590	3.397123	0.0006810	0.9999804
ENSG00000140254.12.DUOXA1	13.41342	-1.9084883	0.5853997	-3.260146	0.0011135	0.9999804
ENSG00000159063.14.ALG8	112.93939	0.3323802	0.1024597	3.244010	0.0011786	0.9999804
ENSG00000171533.12.MAP6	26.74399	-1.0291686	0.3193044	-3.223158	0.0012679	0.9999804
ENSG00000172020.13.GAP43	235.62709	-1.3725239	0.4339196	-3.163084	0.0015611	0.9999804
ENSG00000125726.11.CD70	38.93859	-1.7704418	0.5617950	-3.151402	0.0016249	0.9999804
ENSG00000149090.12.PAMR1	323.14328	-2.2069636	0.7052207	-3.129465	0.0017512	0.9999804
ENSG00000101144.13.BMP7	25.11222	-1.7210234	0.5510064	-3.123418	0.0017876	0.9999804
ENSG00000183072.10.NKX2.5	12.38402	-2.2926770	0.7341754	-3.122792	0.0017914	0.9999804
ENSG00000103540.16.CCP110	121.13915	0.2906640	0.0932682	3.116431	0.0018305	0.9999804

message("here is the model spec:")

## here is the model spec:

dds <- DESeqDataSetFromMatrix(countData = x2c , colData = ss2c, design = ~ Age + Sex + CRP + Metabolic_Syndrome )

## converting counts to integer mode

## Warning in DESeqDataSet(se, design = design, ignoreRank): some variables in
## design formula are characters, converting to factors

##   the design formula contains one or more numeric variables with integer values,
##   specifying a model with increasing fold change for higher values.
##   did you mean for this to be a factor? if so, first convert
##   this variable to a factor using the factor() function

##   the design formula contains one or more numeric variables that have mean or
##   standard deviation larger than 5 (an arbitrary threshold to trigger this message).
##   Including numeric variables with large mean can induce collinearity with the intercept.
##   Users should center and scale numeric variables in the design to improve GLM convergence.

res <- DESeq(dds)

## estimating size factors

## estimating dispersions

## gene-wise dispersion estimates

## mean-dispersion relationship

## final dispersion estimates

## fitting model and testing

z<- results(res)
vsd <- vst(dds, blind=FALSE)
zz <- cbind(as.data.frame(z),assay(vsd))
dge <- as.data.frame(zz[order(zz$pvalue),])

dge[1:20,1:6] %>%
  kbl(caption = "Top DEGs in bone between OA patients with and without metabolic syndrome, adjusted for age, sex and CRP.") %>%
  kable_paper("hover", full_width = F)

Top DEGs in bone between OA patients with and without metabolic syndrome, adjusted for age, sex and CRP.

	baseMean	log2FoldChange	lfcSE	stat	pvalue	padj
ENSG00000203812.2.H2AC18	15.61564	-4.4182659	1.0336522	-4.274422	0.0000192	0.3098525
ENSG00000135480.16.KRT7	26.26632	-2.0953587	0.5318943	-3.939427	0.0000817	0.4412672
ENSG00000198121.13.LPAR1	765.32020	-0.7242177	0.1843492	-3.928510	0.0000855	0.4412672
ENSG00000260266.1.PPIAP46	28.56331	1.4338041	0.3726096	3.848006	0.0001191	0.4412672
ENSG00000133063.16.CHIT1	19.87184	2.9820708	0.7914467	3.767873	0.0001646	0.4412672
ENSG00000181634.8.TNFSF15	99.83771	1.4552388	0.3889060	3.741878	0.0001827	0.4412672
ENSG00000109472.14.CPE	197.99383	1.2409169	0.3326334	3.730584	0.0001910	0.4412672
ENSG00000197614.11.MFAP5	1259.04222	-2.4854321	0.6815676	-3.646641	0.0002657	0.5369949
ENSG00000218336.9.TENM3	19.03004	1.4454954	0.4010120	3.604619	0.0003126	0.5616232
ENSG00000181195.11.PENK	41.98586	2.5020799	0.7244314	3.453854	0.0005526	0.8356607
ENSG00000162545.6.CAMK2N1	75.26906	-1.6312015	0.4761735	-3.425645	0.0006133	0.8356607
ENSG00000148357.16.HMCN2	551.37442	-1.7818720	0.5227430	-3.408696	0.0006527	0.8356607
ENSG00000274422.1.AC245060.5	487.41427	1.4959447	0.4407833	3.393832	0.0006892	0.8356607
ENSG00000183688.4.RFLNB	145.76873	-1.6084987	0.4758178	-3.380492	0.0007236	0.8356607
ENSG00000267339.7.LINC00906	10.54983	-2.4460215	0.7334720	-3.334853	0.0008534	0.8662717
ENSG00000135916.16.ITM2C	307.48864	-1.4756737	0.4451913	-3.314696	0.0009174	0.8662717
ENSG00000124214.21.STAU1	498.95136	-0.2358579	0.0711775	-3.313658	0.0009208	0.8662717
ENSG00000159063.14.ALG8	112.93939	0.3588266	0.1087116	3.300720	0.0009644	0.8662717
ENSG00000169071.15.ROR2	25.21287	2.1959724	0.6696037	3.279511	0.0010399	0.8849324
ENSG00000145113.22.MUC4	14.16622	-1.8667078	0.5818057	-3.208473	0.0013344	0.9499071

dge2c <- dge

Session information

For reproducibility.

sessionInfo()

## R version 4.3.1 (2023-06-16)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.3 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0 
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
## 
## locale:
##  [1] LC_CTYPE=en_AU.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_AU.UTF-8        LC_COLLATE=en_AU.UTF-8    
##  [5] LC_MONETARY=en_AU.UTF-8    LC_MESSAGES=en_AU.UTF-8   
##  [7] LC_PAPER=en_AU.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C       
## 
## time zone: Australia/Melbourne
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats4    stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] pkgload_1.3.2.1             GGally_2.1.2               
##  [3] beeswarm_0.4.0              gtools_3.9.4               
##  [5] echarts4r_0.4.5             kableExtra_1.3.4           
##  [7] topconfects_1.16.0          limma_3.56.2               
##  [9] eulerr_7.0.0                mitch_1.12.0               
## [11] MASS_7.3-60                 fgsea_1.26.0               
## [13] gplots_3.1.3                DESeq2_1.40.2              
## [15] SummarizedExperiment_1.30.2 Biobase_2.60.0             
## [17] MatrixGenerics_1.12.3       matrixStats_1.0.0          
## [19] GenomicRanges_1.52.0        GenomeInfoDb_1.36.3        
## [21] IRanges_2.34.1              S4Vectors_0.38.1           
## [23] BiocGenerics_0.46.0         reshape2_1.4.4             
## [25] lubridate_1.9.2             forcats_1.0.0              
## [27] stringr_1.5.0               dplyr_1.1.3                
## [29] purrr_1.0.2                 readr_2.1.4                
## [31] tidyr_1.3.0                 tibble_3.2.1               
## [33] ggplot2_3.4.3               tidyverse_2.0.0            
## [35] zoo_1.8-12                  R.utils_2.12.2             
## [37] R.oo_1.25.0                 R.methodsS3_1.8.2          
## 
## loaded via a namespace (and not attached):
##  [1] bitops_1.0-7            gridExtra_2.3           rlang_1.1.1            
##  [4] magrittr_2.0.3          compiler_4.3.1          systemfonts_1.0.4      
##  [7] vctrs_0.6.3             rvest_1.0.3             pkgconfig_2.0.3        
## [10] crayon_1.5.2            fastmap_1.1.1           XVector_0.40.0         
## [13] ellipsis_0.3.2          caTools_1.18.2          utf8_1.2.3             
## [16] promises_1.2.1          rmarkdown_2.24          tzdb_0.4.0             
## [19] xfun_0.40               zlibbioc_1.46.0         cachem_1.0.8           
## [22] jsonlite_1.8.7          highr_0.10              later_1.3.1            
## [25] DelayedArray_0.26.7     reshape_0.8.9           BiocParallel_1.34.2    
## [28] parallel_4.3.1          R6_2.5.1                bslib_0.5.1            
## [31] stringi_1.7.12          RColorBrewer_1.1-3      jquerylib_0.1.4        
## [34] assertthat_0.2.1        Rcpp_1.0.11             knitr_1.44             
## [37] httpuv_1.6.11           Matrix_1.6-1            timechange_0.2.0       
## [40] tidyselect_1.2.0        rstudioapi_0.15.0       abind_1.4-5            
## [43] yaml_2.3.7              codetools_0.2-19        lattice_0.21-8         
## [46] plyr_1.8.8              shiny_1.7.5             withr_2.5.0            
## [49] evaluate_0.21           xml2_1.3.5              pillar_1.9.0           
## [52] KernSmooth_2.23-22      generics_0.1.3          RCurl_1.98-1.12        
## [55] hms_1.1.3               munsell_0.5.0           scales_1.2.1           
## [58] xtable_1.8-4            glue_1.6.2              tools_4.3.1            
## [61] data.table_1.14.8       webshot_0.5.5           locfit_1.5-9.8         
## [64] fastmatch_1.1-4         cowplot_1.1.1           grid_4.3.1             
## [67] colorspace_2.1-0        GenomeInfoDbData_1.2.10 cli_3.6.1              
## [70] fansi_1.0.4             viridisLite_0.4.2       S4Arrays_1.0.6         
## [73] svglite_2.1.1           gtable_0.3.4            sass_0.4.7             
## [76] digest_0.6.33           htmlwidgets_1.6.2       htmltools_0.5.6        
## [79] lifecycle_1.0.3         httr_1.4.7              mime_0.12