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library("DESeq2")## Loading required package: S4Vectors## Loading required package: stats4## Loading required package: BiocGenerics##
## Attaching package: 'BiocGenerics'## The following objects are masked from 'package:stats':
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## IQR, mad, sd, var, xtabs## The following objects are masked from 'package:base':
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## anyDuplicated, append, as.data.frame, basename, cbind, colnames,
## dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
## grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
## order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
## rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
## union, unique, unsplit, which.max, which.min##
## Attaching package: 'S4Vectors'## The following objects are masked from 'package:base':
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## expand.grid, I, unname## Loading required package: IRanges## Loading required package: GenomicRanges## Loading required package: GenomeInfoDb## Loading required package: SummarizedExperiment## Loading required package: MatrixGenerics## Loading required package: matrixStats##
## Attaching package: 'MatrixGenerics'## The following objects are masked from 'package:matrixStats':
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## colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
## colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
## colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
## colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
## colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
## colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
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## colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
## rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
## rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
## rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
## rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
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## rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
## rowWeightedSds, rowWeightedVars## Loading required package: Biobase## Welcome to Bioconductor
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## Vignettes contain introductory material; view with
## 'browseVignettes()'. To cite Bioconductor, see
## 'citation("Biobase")', and for packages 'citation("pkgname")'.##
## Attaching package: 'Biobase'## The following object is masked from 'package:MatrixGenerics':
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## rowMedians## The following objects are masked from 'package:matrixStats':
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## anyMissing, rowMedianslibrary("mitch")## Registered S3 method overwritten by 'GGally':
## method from
## +.gg ggplot2library("dplyr")##
## Attaching package: 'dplyr'## The following object is masked from 'package:Biobase':
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## combine## The following object is masked from 'package:matrixStats':
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## count## The following objects are masked from 'package:GenomicRanges':
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## first, intersect, rename, setdiff, setequal, union## The following objects are masked from 'package:BiocGenerics':
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## combine, intersect, setdiff, union## The following objects are masked from 'package:stats':
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## intersect, setdiff, setequal, unionlibrary("kableExtra")##
## Attaching package: 'kableExtra'## The following object is masked from 'package:dplyr':
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## group_rowsdownload.file(url = "https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE118089&format=file&file=GSE118089%5Fstan%5Fmziemann%5F2018%5Fcountmatrix%2Etsv%2Egz",
destfile="GSE118089.tsv")
x <- read.table("GSE118089.tsv",header=TRUE,row.names=1)
head(x)## CtrlPMX_rep1 CtrlPMX_rep2 CtrlPMX_rep3 CtrlPMX_rep4
## ENSMUSG00000000001_Gnai3 1093 1180 1189 1317
## ENSMUSG00000000003_Pbsn 0 0 0 0
## ENSMUSG00000000028_Cdc45 25 22 32 17
## ENSMUSG00000000031_H19 0 0 0 0
## ENSMUSG00000000037_Scml2 2 3 3 4
## ENSMUSG00000000049_Apoh 132 157 218 194
## CtrlPMX_rep5 CtrlPMX_rep6 CtrlUntr_rep1 CtrlUntr_rep2
## ENSMUSG00000000001_Gnai3 1116 1273 1293 1150
## ENSMUSG00000000003_Pbsn 0 0 0 0
## ENSMUSG00000000028_Cdc45 25 24 16 20
## ENSMUSG00000000031_H19 0 0 0 0
## ENSMUSG00000000037_Scml2 2 1 3 4
## ENSMUSG00000000049_Apoh 67 89 226 148
## CtrlUntr_rep3 CtrlUntr_rep4 CtrlUntr_rep5
## ENSMUSG00000000001_Gnai3 914 1089 1080
## ENSMUSG00000000003_Pbsn 0 0 0
## ENSMUSG00000000028_Cdc45 12 14 19
## ENSMUSG00000000031_H19 0 0 1
## ENSMUSG00000000037_Scml2 3 2 6
## ENSMUSG00000000049_Apoh 137 186 72
## CtrlUntr_rep6 DiabPMX_rep1 DiabPMX_rep2 DiabPMX_rep3
## ENSMUSG00000000001_Gnai3 1087 1126 834 1255
## ENSMUSG00000000003_Pbsn 0 0 0 0
## ENSMUSG00000000028_Cdc45 25 22 18 20
## ENSMUSG00000000031_H19 0 0 0 1
## ENSMUSG00000000037_Scml2 3 6 3 4
## ENSMUSG00000000049_Apoh 161 22 30 69
## DiabPMX_rep4 DiabPMX_rep5 DiabPMX_rep6 DiabUntr_rep1
## ENSMUSG00000000001_Gnai3 1187 1121 837 1205
## ENSMUSG00000000003_Pbsn 0 0 0 0
## ENSMUSG00000000028_Cdc45 17 18 20 14
## ENSMUSG00000000031_H19 1 0 2 0
## ENSMUSG00000000037_Scml2 4 8 5 3
## ENSMUSG00000000049_Apoh 64 51 22 50
## DiabUntr_rep2 DiabUntr_rep3 DiabUntr_rep4
## ENSMUSG00000000001_Gnai3 1465 1261 1071
## ENSMUSG00000000003_Pbsn 0 0 0
## ENSMUSG00000000028_Cdc45 37 28 24
## ENSMUSG00000000031_H19 2 0 0
## ENSMUSG00000000037_Scml2 2 8 2
## ENSMUSG00000000049_Apoh 31 21 123
## DiabUntr_rep5 DiabUntr_rep6
## ENSMUSG00000000001_Gnai3 1346 1460
## ENSMUSG00000000003_Pbsn 0 0
## ENSMUSG00000000028_Cdc45 25 25
## ENSMUSG00000000031_H19 0 1
## ENSMUSG00000000037_Scml2 3 4
## ENSMUSG00000000049_Apoh 168 37ss <- as.data.frame(colnames(x))
colnames(ss) <- "samplename"
ss$grp <- sapply(strsplit(colnames(x),"_"),"[[",1)
# contrast 1 is non-diabetic versus diabetic
ss1 <- subset(ss,grp=="CtrlUntr" | grp=="DiabUntr")
ss1$trt <- as.factor(grepl("Diab",ss1$grp))
xx1 <- x[,which(colnames(x) %in% ss1$samplename)]
#xx2 <- xx2[which(rowMeans(xx2)>10),]
ss1## samplename grp trt
## 7 CtrlUntr_rep1 CtrlUntr FALSE
## 8 CtrlUntr_rep2 CtrlUntr FALSE
## 9 CtrlUntr_rep3 CtrlUntr FALSE
## 10 CtrlUntr_rep4 CtrlUntr FALSE
## 11 CtrlUntr_rep5 CtrlUntr FALSE
## 12 CtrlUntr_rep6 CtrlUntr FALSE
## 19 DiabUntr_rep1 DiabUntr TRUE
## 20 DiabUntr_rep2 DiabUntr TRUE
## 21 DiabUntr_rep3 DiabUntr TRUE
## 22 DiabUntr_rep4 DiabUntr TRUE
## 23 DiabUntr_rep5 DiabUntr TRUE
## 24 DiabUntr_rep6 DiabUntr TRUEhead(xx1)## CtrlUntr_rep1 CtrlUntr_rep2 CtrlUntr_rep3
## ENSMUSG00000000001_Gnai3 1293 1150 914
## ENSMUSG00000000003_Pbsn 0 0 0
## ENSMUSG00000000028_Cdc45 16 20 12
## ENSMUSG00000000031_H19 0 0 0
## ENSMUSG00000000037_Scml2 3 4 3
## ENSMUSG00000000049_Apoh 226 148 137
## CtrlUntr_rep4 CtrlUntr_rep5 CtrlUntr_rep6
## ENSMUSG00000000001_Gnai3 1089 1080 1087
## ENSMUSG00000000003_Pbsn 0 0 0
## ENSMUSG00000000028_Cdc45 14 19 25
## ENSMUSG00000000031_H19 0 1 0
## ENSMUSG00000000037_Scml2 2 6 3
## ENSMUSG00000000049_Apoh 186 72 161
## DiabUntr_rep1 DiabUntr_rep2 DiabUntr_rep3
## ENSMUSG00000000001_Gnai3 1205 1465 1261
## ENSMUSG00000000003_Pbsn 0 0 0
## ENSMUSG00000000028_Cdc45 14 37 28
## ENSMUSG00000000031_H19 0 2 0
## ENSMUSG00000000037_Scml2 3 2 8
## ENSMUSG00000000049_Apoh 50 31 21
## DiabUntr_rep4 DiabUntr_rep5 DiabUntr_rep6
## ENSMUSG00000000001_Gnai3 1071 1346 1460
## ENSMUSG00000000003_Pbsn 0 0 0
## ENSMUSG00000000028_Cdc45 24 25 25
## ENSMUSG00000000031_H19 0 0 1
## ENSMUSG00000000037_Scml2 2 3 4
## ENSMUSG00000000049_Apoh 123 168 37# contrast 2 is diabetic versus diabetic treated with PMC53
ss2 <- subset(ss,grp=="DiabUntr" | grp=="DiabPMX")
ss2$trt <- as.factor(grepl("PMX",ss2$grp))
xx2 <- x[,which(colnames(x) %in% ss2$samplename)]
#xx2 <- xx2[which(rowMeans(xx2)>10),]
ss2## samplename grp trt
## 13 DiabPMX_rep1 DiabPMX TRUE
## 14 DiabPMX_rep2 DiabPMX TRUE
## 15 DiabPMX_rep3 DiabPMX TRUE
## 16 DiabPMX_rep4 DiabPMX TRUE
## 17 DiabPMX_rep5 DiabPMX TRUE
## 18 DiabPMX_rep6 DiabPMX TRUE
## 19 DiabUntr_rep1 DiabUntr FALSE
## 20 DiabUntr_rep2 DiabUntr FALSE
## 21 DiabUntr_rep3 DiabUntr FALSE
## 22 DiabUntr_rep4 DiabUntr FALSE
## 23 DiabUntr_rep5 DiabUntr FALSE
## 24 DiabUntr_rep6 DiabUntr FALSEhead(xx2)## DiabPMX_rep1 DiabPMX_rep2 DiabPMX_rep3 DiabPMX_rep4
## ENSMUSG00000000001_Gnai3 1126 834 1255 1187
## ENSMUSG00000000003_Pbsn 0 0 0 0
## ENSMUSG00000000028_Cdc45 22 18 20 17
## ENSMUSG00000000031_H19 0 0 1 1
## ENSMUSG00000000037_Scml2 6 3 4 4
## ENSMUSG00000000049_Apoh 22 30 69 64
## DiabPMX_rep5 DiabPMX_rep6 DiabUntr_rep1 DiabUntr_rep2
## ENSMUSG00000000001_Gnai3 1121 837 1205 1465
## ENSMUSG00000000003_Pbsn 0 0 0 0
## ENSMUSG00000000028_Cdc45 18 20 14 37
## ENSMUSG00000000031_H19 0 2 0 2
## ENSMUSG00000000037_Scml2 8 5 3 2
## ENSMUSG00000000049_Apoh 51 22 50 31
## DiabUntr_rep3 DiabUntr_rep4 DiabUntr_rep5
## ENSMUSG00000000001_Gnai3 1261 1071 1346
## ENSMUSG00000000003_Pbsn 0 0 0
## ENSMUSG00000000028_Cdc45 28 24 25
## ENSMUSG00000000031_H19 0 0 0
## ENSMUSG00000000037_Scml2 8 2 3
## ENSMUSG00000000049_Apoh 21 123 168
## DiabUntr_rep6
## ENSMUSG00000000001_Gnai3 1460
## ENSMUSG00000000003_Pbsn 0
## ENSMUSG00000000028_Cdc45 25
## ENSMUSG00000000031_H19 1
## ENSMUSG00000000037_Scml2 4
## ENSMUSG00000000049_Apoh 37Run DE analysis
# contrast 1
dds <- DESeqDataSetFromMatrix(countData = xx1 , colData = ss1, design = ~ trt )
res <- DESeq(dds)## estimating size factors## estimating dispersions## gene-wise dispersion estimates## mean-dispersion relationship## final dispersion estimates## fitting model and testingz<- results(res)
vsd <- vst(dds, blind=FALSE)
zz <- cbind(as.data.frame(z),assay(vsd))
dge <- as.data.frame(zz[order(zz$pvalue),])
head(dge,10)## baseMean log2FoldChange lfcSE stat
## ENSMUSG00000025453_Nnt 2908.02070 1.245600 0.04873625 25.55799
## ENSMUSG00000029456_Acad10 739.10509 -2.428930 0.09504866 -25.55459
## ENSMUSG00000017929_B4galt5 1709.27639 -1.860560 0.08006758 -23.23737
## ENSMUSG00000023067_Cdkn1a 341.48531 3.578513 0.19339272 18.50387
## ENSMUSG00000073643_Wdfy1 839.65967 1.295093 0.07001707 18.49682
## ENSMUSG00000038776_Ephx1 834.28830 2.221397 0.12019941 18.48094
## ENSMUSG00000053279_Aldh1a1 583.42567 2.846482 0.16715139 17.02937
## ENSMUSG00000034457_Eda2r 78.00454 3.149025 0.18968483 16.60135
## ENSMUSG00000017390_Aldoc 126.46764 1.969574 0.14044646 14.02366
## ENSMUSG00000028553_Angptl3 115.77935 2.361842 0.17035149 13.86452
## pvalue padj CtrlUntr_rep1
## ENSMUSG00000025453_Nnt 4.475752e-144 5.093687e-140 10.825867
## ENSMUSG00000029456_Acad10 4.882050e-144 5.093687e-140 10.486111
## ENSMUSG00000017929_B4galt5 1.909154e-119 1.327944e-115 11.673091
## ENSMUSG00000023067_Cdkn1a 1.921843e-76 9.140405e-73 7.471190
## ENSMUSG00000073643_Wdfy1 2.190158e-76 9.140405e-73 9.239526
## ENSMUSG00000038776_Ephx1 2.940404e-76 1.022623e-72 8.445448
## ENSMUSG00000053279_Aldh1a1 4.974004e-65 1.482751e-61 8.056788
## ENSMUSG00000034457_Eda2r 6.813907e-62 1.777322e-58 6.441342
## ENSMUSG00000017390_Aldoc 1.116970e-44 2.589756e-41 7.073569
## ENSMUSG00000028553_Angptl3 1.039151e-43 2.168396e-40 6.943748
## CtrlUntr_rep2 CtrlUntr_rep3 CtrlUntr_rep4
## ENSMUSG00000025453_Nnt 10.883609 10.902008 10.784909
## ENSMUSG00000029456_Acad10 10.272884 10.434241 10.380339
## ENSMUSG00000017929_B4galt5 11.392385 11.320996 11.466744
## ENSMUSG00000023067_Cdkn1a 7.064772 6.885848 7.079425
## ENSMUSG00000073643_Wdfy1 9.087368 9.234962 9.195653
## ENSMUSG00000038776_Ephx1 8.647438 8.616624 8.705959
## ENSMUSG00000053279_Aldh1a1 7.834841 7.669067 7.931195
## ENSMUSG00000034457_Eda2r 6.514404 6.570329 6.413605
## ENSMUSG00000017390_Aldoc 7.039712 7.080032 6.940763
## ENSMUSG00000028553_Angptl3 7.014046 6.811798 7.026135
## CtrlUntr_rep5 CtrlUntr_rep6 DiabUntr_rep1
## ENSMUSG00000025453_Nnt 10.854254 10.751312 12.093445
## ENSMUSG00000029456_Acad10 10.305639 10.483572 8.312555
## ENSMUSG00000017929_B4galt5 11.272372 11.488567 9.719292
## ENSMUSG00000023067_Cdkn1a 7.004038 6.876049 9.697477
## ENSMUSG00000073643_Wdfy1 9.141127 9.239482 10.363835
## ENSMUSG00000038776_Ephx1 8.821032 8.367145 10.437900
## ENSMUSG00000053279_Aldh1a1 8.083080 7.542202 10.231231
## ENSMUSG00000034457_Eda2r 6.422391 6.454757 7.911158
## ENSMUSG00000017390_Aldoc 7.175417 7.112012 8.179015
## ENSMUSG00000028553_Angptl3 6.779467 6.635185 7.897905
## DiabUntr_rep2 DiabUntr_rep3 DiabUntr_rep4
## ENSMUSG00000025453_Nnt 12.128164 11.967625 12.035900
## ENSMUSG00000029456_Acad10 8.126028 8.159646 8.484397
## ENSMUSG00000017929_B4galt5 9.807044 9.716448 9.803545
## ENSMUSG00000023067_Cdkn1a 9.847079 9.503857 9.092454
## ENSMUSG00000073643_Wdfy1 10.431679 10.407184 10.190536
## ENSMUSG00000038776_Ephx1 10.645217 10.775516 10.167569
## ENSMUSG00000053279_Aldh1a1 10.281855 10.312555 9.479411
## ENSMUSG00000034457_Eda2r 7.974223 7.735623 7.727002
## ENSMUSG00000017390_Aldoc 8.427913 8.127210 8.136706
## ENSMUSG00000028553_Angptl3 8.198151 8.353478 8.005746
## DiabUntr_rep5 DiabUntr_rep6
## ENSMUSG00000025453_Nnt 11.959817 12.009150
## ENSMUSG00000029456_Acad10 8.468857 8.481024
## ENSMUSG00000017929_B4galt5 9.547557 9.653268
## ENSMUSG00000023067_Cdkn1a 9.319871 9.479027
## ENSMUSG00000073643_Wdfy1 10.196129 10.411032
## ENSMUSG00000038776_Ephx1 10.613216 10.440216
## ENSMUSG00000053279_Aldh1a1 10.250941 10.099048
## ENSMUSG00000034457_Eda2r 7.957011 7.792649
## ENSMUSG00000017390_Aldoc 7.997879 8.312550
## ENSMUSG00000028553_Angptl3 8.290578 8.201983dge1 <- dge
# contrast 2
dds <- DESeqDataSetFromMatrix(countData = xx2 , colData = ss2, design = ~ trt )
res <- DESeq(dds)## estimating size factors## estimating dispersions## gene-wise dispersion estimates## mean-dispersion relationship## final dispersion estimates## fitting model and testingz<- results(res)
vsd <- vst(dds, blind=FALSE)
zz <- cbind(as.data.frame(z),assay(vsd))
dge <- as.data.frame(zz[order(zz$pvalue),])
head(dge,10)## baseMean log2FoldChange lfcSE stat
## ENSMUSG00000025453_Nnt 2988.3007 -1.156044 0.04725936 -24.46170
## ENSMUSG00000029456_Acad10 638.9908 2.162476 0.11051542 19.56719
## ENSMUSG00000073643_Wdfy1 836.6600 -1.354469 0.07912676 -17.11772
## ENSMUSG00000056999_Ide 1793.0178 1.157567 0.08160812 14.18446
## ENSMUSG00000017929_B4galt5 1211.5587 1.172109 0.09120944 12.85075
## ENSMUSG00000053279_Aldh1a1 658.3801 -1.865866 0.15568745 -11.98469
## ENSMUSG00000023087_Noct 326.3234 -2.076479 0.17821774 -11.65136
## ENSMUSG00000069456_Rdh16 2739.2636 -1.074212 0.09621504 -11.16470
## ENSMUSG00000028553_Angptl3 124.9328 -1.842438 0.16904237 -10.89927
## ENSMUSG00000017390_Aldoc 141.2130 -1.365104 0.12582063 -10.84961
## pvalue padj DiabPMX_rep1
## ENSMUSG00000025453_Nnt 3.778368e-132 7.319832e-128 10.865124
## ENSMUSG00000029456_Acad10 2.944649e-85 2.852334e-81 9.992488
## ENSMUSG00000073643_Wdfy1 1.094881e-65 7.070374e-62 9.008366
## ENSMUSG00000056999_Ide 1.143410e-45 5.537819e-42 11.367345
## ENSMUSG00000017929_B4galt5 8.518583e-38 3.300610e-34 11.015373
## ENSMUSG00000053279_Aldh1a1 4.274291e-33 1.380097e-29 8.787975
## ENSMUSG00000023087_Noct 2.258293e-31 6.249988e-28 7.497448
## ENSMUSG00000069456_Rdh16 6.069706e-29 1.469855e-25 10.791058
## ENSMUSG00000028553_Angptl3 1.161853e-27 2.500953e-24 6.893295
## ENSMUSG00000017390_Aldoc 2.002884e-27 3.880187e-24 7.239468
## DiabPMX_rep2 DiabPMX_rep3 DiabPMX_rep4 DiabPMX_rep5
## ENSMUSG00000025453_Nnt 10.914253 10.896440 10.987304 10.999448
## ENSMUSG00000029456_Acad10 10.104074 10.191074 10.436843 10.087527
## ENSMUSG00000073643_Wdfy1 9.122613 9.224170 9.301376 9.014461
## ENSMUSG00000056999_Ide 11.461997 11.081605 11.396441 11.420112
## ENSMUSG00000017929_B4galt5 10.903271 10.804816 10.678911 10.484287
## ENSMUSG00000053279_Aldh1a1 8.554285 8.624737 8.487722 8.143909
## ENSMUSG00000023087_Noct 7.551428 7.862917 7.659562 8.000887
## ENSMUSG00000069456_Rdh16 10.717401 10.874074 10.950176 10.819799
## ENSMUSG00000028553_Angptl3 7.008650 7.120368 7.273984 7.189476
## ENSMUSG00000017390_Aldoc 7.412681 7.276321 7.312747 7.324672
## DiabPMX_rep6 DiabUntr_rep1 DiabUntr_rep2
## ENSMUSG00000025453_Nnt 10.889002 12.101595 12.137937
## ENSMUSG00000029456_Acad10 10.065203 8.295439 8.106785
## ENSMUSG00000073643_Wdfy1 9.117871 10.366900 10.436566
## ENSMUSG00000056999_Ide 11.204640 10.154003 10.199522
## ENSMUSG00000017929_B4galt5 10.808371 9.718428 9.808253
## ENSMUSG00000053279_Aldh1a1 8.593863 10.233613 10.285989
## ENSMUSG00000023087_Noct 7.647917 9.213709 9.304922
## ENSMUSG00000069456_Rdh16 10.992068 11.926795 11.926221
## ENSMUSG00000028553_Angptl3 6.759323 7.873130 8.180223
## ENSMUSG00000017390_Aldoc 7.422691 8.159601 8.413867
## DiabUntr_rep3 DiabUntr_rep4 DiabUntr_rep5
## ENSMUSG00000025453_Nnt 11.974613 12.047500 11.970626
## ENSMUSG00000029456_Acad10 8.139191 8.472774 8.456475
## ENSMUSG00000073643_Wdfy1 10.409545 10.196035 10.201036
## ENSMUSG00000056999_Ide 10.365046 10.380938 10.176444
## ENSMUSG00000017929_B4galt5 9.714689 9.806543 9.547941
## ENSMUSG00000053279_Aldh1a1 10.314453 9.479795 10.256153
## ENSMUSG00000023087_Noct 9.089563 8.985992 9.034613
## ENSMUSG00000069456_Rdh16 12.013290 11.451540 11.912987
## ENSMUSG00000028553_Angptl3 8.336309 7.985580 8.275249
## ENSMUSG00000017390_Aldoc 8.106173 8.119085 7.977095
## DiabUntr_rep6
## ENSMUSG00000025453_Nnt 12.021026
## ENSMUSG00000029456_Acad10 8.469598
## ENSMUSG00000073643_Wdfy1 10.418008
## ENSMUSG00000056999_Ide 10.107143
## ENSMUSG00000017929_B4galt5 9.655412
## ENSMUSG00000053279_Aldh1a1 10.104311
## ENSMUSG00000023087_Noct 9.841711
## ENSMUSG00000069456_Rdh16 12.064578
## ENSMUSG00000028553_Angptl3 8.185806
## ENSMUSG00000017390_Aldoc 8.298338dge2 <- dgegt <- as.data.frame(rownames(x))
head(gt)## rownames(x)
## 1 ENSMUSG00000000001_Gnai3
## 2 ENSMUSG00000000003_Pbsn
## 3 ENSMUSG00000000028_Cdc45
## 4 ENSMUSG00000000031_H19
## 5 ENSMUSG00000000037_Scml2
## 6 ENSMUSG00000000049_Apohgt$gene <- sapply(strsplit(rownames(x),"_"),"[[",2)
xl <- list("diab"=dge1,"PMX"=dge2)
m <- mitch_import(x=xl,DEtype = "deseq2", geneTable = gt)## Note: Mean no. genes in input = 48526## Note: no. genes in output = 28178## Note: estimated proportion of input genes in output = 0.581head(m)## diab PMX
## 0610006L08Rik -5.5412223 1.7043723
## 0610007P14Rik -0.5043192 0.5154128
## 0610009B22Rik -1.1468556 0.7601283
## 0610009E02Rik -1.0617246 0.7364015
## 0610009L18Rik -3.4134523 2.9613348
## 0610009O20Rik -1.1413048 1.7889029# reactome converted to human on 22nd Sept
genesets <- gmt_import("ReactomePathways_mouse.gmt")
head(genesets)## $`2-LTR-circle-formation`
## [1] "Banf1" "Hmga1" "Lig4" "Psip1" "Xrcc4" "Xrcc5" "Xrcc6"
##
## $`5-Phosphoribose-1-diphosphate-biosynthesis`
## [1] "Prps1l1" "Prps1l3" "Prps2"
##
## $`A-tetrasaccharide-linker-sequence-is-required-for-GAG-synthesis`
## [1] "Agrn" "B3galt6" "B3gat1" "B3gat2" "B3gat3" "B4galt7" "Bcan"
## [8] "Bgn" "Cspg4" "Cspg5" "Dcn" "Gm43720" "Gpc1" "Gpc3"
## [15] "Gpc4" "Gpc5" "Gpc6" "Hspg2" "Ncan" "Sdc1" "Sdc2"
## [22] "Sdc3" "Sdc4" "Vcan" "Xylt1" "Xylt2"
##
## $`ABC-transporter-disorders`
## [1] "Abca1" "Abca12" "Abca3" "Abcb11" "Abcb4" "Abcb6" "Abcc2" "Abcc6"
## [9] "Abcc8" "Abcc9" "Abcd1" "Abcd4" "Abcg5" "Abcg8" "Apoa1" "Cftr"
## [17] "Derl1" "Derl2" "Derl3" "Erlec1" "Erlin1" "Erlin2" "Kcnj11" "Lmbrd1"
## [25] "Os9" "Psma1" "Psma2" "Psma3" "Psma4" "Psma5" "Psma6" "Psma7"
## [33] "Psma8" "Psmb1" "Psmb10" "Psmb11" "Psmb2" "Psmb3" "Psmb4" "Psmb5"
## [41] "Psmb6" "Psmb7" "Psmb8" "Psmb9" "Psmc1" "Psmc2" "Psmc3" "Psmc4"
## [49] "Psmc5" "Psmc6" "Psmd1" "Psmd10" "Psmd11" "Psmd12" "Psmd13" "Psmd14"
## [57] "Psmd2" "Psmd3" "Psmd4" "Psmd5" "Psmd6" "Psmd7" "Psmd8" "Psmd9"
## [65] "Psme1" "Psme2b" "Psme3" "Psme4" "Psmf1" "Rnf185" "Rnf5" "Rps27a"
## [73] "Sel1l" "Uba52" "Ubb" "Vcp"
##
## $`ABC-transporters-in-lipid-homeostasis`
## [1] "Abca12" "Abca2" "Abca3" "Abca5" "Abca6" "Abca7" "Abca9" "Abcd1"
## [9] "Abcd2" "Abcd3" "Abcg1" "Abcg4" "Abcg5" "Abcg8" "Apoa1" "Pex19"
## [17] "Pex3"
##
## $`ABC-family-proteins-mediated-transport`
## [1] "Abca12" "Abca2" "Abca3" "Abca4" "Abca5" "Abca6" "Abca7"
## [8] "Abca8b" "Abca9" "Abcb10" "Abcb1a" "Abcb4" "Abcb5" "Abcb6"
## [15] "Abcb7" "Abcb8" "Abcb9" "Abcc2" "Abcc3" "Abcc4" "Abcc5"
## [22] "Abcc6" "Abcc9" "Abcd1" "Abcd2" "Abcd3" "Abcf1" "Abcg1"
## [29] "Abcg4" "Abcg5" "Abcg8" "Apoa1" "Cftr" "Derl1" "Derl2"
## [36] "Derl3" "Eif2s1" "Eif2s2" "Eif2s3x" "Erlec1" "Erlin1" "Erlin2"
## [43] "Kcnj11" "Os9" "Pex19" "Pex3" "Psma1" "Psma2" "Psma3"
## [50] "Psma4" "Psma5" "Psma6" "Psma7" "Psma8" "Psmb1" "Psmb10"
## [57] "Psmb11" "Psmb2" "Psmb3" "Psmb4" "Psmb5" "Psmb6" "Psmb7"
## [64] "Psmb8" "Psmb9" "Psmc1" "Psmc2" "Psmc3" "Psmc4" "Psmc5"
## [71] "Psmc6" "Psmd1" "Psmd10" "Psmd11" "Psmd12" "Psmd13" "Psmd14"
## [78] "Psmd2" "Psmd3" "Psmd4" "Psmd5" "Psmd6" "Psmd7" "Psmd8"
## [85] "Psmd9" "Psme1" "Psme2b" "Psme3" "Psme4" "Psmf1" "Rnf185"
## [92] "Rnf5" "Rps27a" "Sel1l" "Uba52" "Ubb" "Vcp"res <- mitch_calc(m,genesets , priority = "effect")## Note: Enrichments with large effect sizes may not be
## statistically significant.head(res$enrichment_result,50) %>% kbl() %>% kable_paper("hover", full_width = F)| set | setSize | pMANOVA | s.diab | s.PMX | p.diab | p.PMX | s.dist | SD | p.adjustMANOVA | |
|---|---|---|---|---|---|---|---|---|---|---|
| 1431 | Viral-mRNA-Translation | 73 | 0.0000000 | 0.7014620 | -0.8022903 | 0.0000000 | 0.0000000 | 1.0657010 | 1.0633135 | 0.0000000 |
| 860 | Peptide-chain-elongation | 73 | 0.0000000 | 0.6989898 | -0.7890377 | 0.0000000 | 0.0000000 | 1.0541192 | 1.0521944 | 0.0000000 |
| 1096 | Response-of-EIF2AK4-(GCN2)-to-amino-acid-deficiency | 85 | 0.0000000 | 0.6652396 | -0.7566319 | 0.0000000 | 0.0000000 | 1.0074897 | 1.0054150 | 0.0000000 |
| 381 | Eukaryotic-Translation-Elongation | 77 | 0.0000000 | 0.6654239 | -0.7529034 | 0.0000000 | 0.0000000 | 1.0048147 | 1.0029089 | 0.0000000 |
| 429 | Formation-of-a-pool-of-free-40S-subunits | 85 | 0.0000000 | 0.6529024 | -0.7251457 | 0.0000000 | 0.0000000 | 0.9757653 | 0.9744272 | 0.0000000 |
| 383 | Eukaryotic-Translation-Termination | 77 | 0.0000000 | 0.6462038 | -0.7227561 | 0.0000000 | 0.0000000 | 0.9695132 | 0.9680008 | 0.0000000 |
| 434 | Formation-of-the-ternary-complex,-and-subsequently,-the-43S-complex | 46 | 0.0000000 | 0.6599007 | -0.7006813 | 0.0000000 | 0.0000000 | 0.9625088 | 0.9620767 | 0.0000000 |
| 1150 | Selenocysteine-synthesis | 76 | 0.0000000 | 0.6236080 | -0.6963243 | 0.0000000 | 0.0000000 | 0.9347483 | 0.9333331 | 0.0000000 |
| 791 | Nonsense-Mediated-Decay-(NMD)-independent-of-the-Exon-Junction-Complex-(EJC) | 79 | 0.0000000 | 0.6165137 | -0.6895551 | 0.0000000 | 0.0000000 | 0.9249732 | 0.9235301 | 0.0000000 |
| 878 | Phosphorylation-of-CD3-and-TCR-zeta-chains | 17 | 0.0000014 | -0.5234523 | 0.7270485 | 0.0001859 | 0.0000002 | 0.8958805 | 0.8842376 | 0.0000402 |
| 470 | GTP-hydrolysis-and-joining-of-the-60S-ribosomal-subunit | 96 | 0.0000000 | 0.5778998 | -0.6840451 | 0.0000000 | 0.0000000 | 0.8954808 | 0.8923298 | 0.0000000 |
| 829 | PD-1-signaling | 17 | 0.0000026 | -0.5551608 | 0.7022791 | 0.0000737 | 0.0000005 | 0.8952092 | 0.8891443 | 0.0000741 |
| 1392 | Translocation-of-ZAP-70-to-Immunological-synapse | 14 | 0.0000205 | -0.5349712 | 0.7141285 | 0.0005273 | 0.0000037 | 0.8922856 | 0.8832468 | 0.0003383 |
| 630 | L13a-mediated-translational-silencing-of-Ceruloplasmin-expression | 95 | 0.0000000 | 0.5736949 | -0.6707032 | 0.0000000 | 0.0000000 | 0.8825920 | 0.8799223 | 0.0000000 |
| 1105 | Ribosomal-scanning-and-start-codon-recognition | 53 | 0.0000000 | 0.5447782 | -0.6408124 | 0.0000000 | 0.0000000 | 0.8410849 | 0.8383392 | 0.0000000 |
| 156 | Cap-dependent-Translation-Initiation | 103 | 0.0000000 | 0.5505129 | -0.6299890 | 0.0000000 | 0.0000000 | 0.8366305 | 0.8347409 | 0.0000000 |
| 382 | Eukaryotic-Translation-Initiation | 103 | 0.0000000 | 0.5505129 | -0.6299890 | 0.0000000 | 0.0000000 | 0.8366305 | 0.8347409 | 0.0000000 |
| 56 | Activation-of-the-mRNA-upon-binding-of-the-cap-binding-complex-and-eIFs,-and-subsequent-binding-to-43S | 54 | 0.0000000 | 0.5405782 | -0.6230674 | 0.0000000 | 0.0000000 | 0.8248866 | 0.8228217 | 0.0000000 |
| 489 | Gluconeogenesis | 30 | 0.0000000 | 0.6001670 | -0.5652255 | 0.0000000 | 0.0000001 | 0.8244272 | 0.8240569 | 0.0000005 |
| 1383 | Translation-initiation-complex-formation | 53 | 0.0000000 | 0.5323478 | -0.6166413 | 0.0000000 | 0.0000000 | 0.8146415 | 0.8124580 | 0.0000000 |
| 32 | Acetylcholine-regulates-insulin-secretion | 10 | 0.0034006 | -0.5200227 | 0.5961375 | 0.0044001 | 0.0010947 | 0.7910774 | 0.7892444 | 0.0202662 |
| 1129 | SRP-dependent-cotranslational-protein-targeting-to-membrane | 96 | 0.0000000 | 0.4649397 | -0.6332259 | 0.0000000 | 0.0000000 | 0.7855851 | 0.7765204 | 0.0000000 |
| 1095 | Response-of-EIF2AK1-(HRI)-to-heme-deficiency | 15 | 0.0002721 | 0.4663163 | -0.5991620 | 0.0017626 | 0.0000585 | 0.7592404 | 0.7534070 | 0.0026530 |
| 790 | Nonsense-Mediated-Decay-(NMD)-enhanced-by-the-Exon-Junction-Complex-(EJC) | 99 | 0.0000000 | 0.5070057 | -0.5638953 | 0.0000000 | 0.0000000 | 0.7583091 | 0.7572413 | 0.0000000 |
| 792 | Nonsense-Mediated-Decay-(NMD) | 99 | 0.0000000 | 0.5070057 | -0.5638953 | 0.0000000 | 0.0000000 | 0.7583091 | 0.7572413 | 0.0000000 |
| 820 | Organic-cation/anion/zwitterion-transport | 12 | 0.0019934 | -0.5017279 | 0.5666702 | 0.0026130 | 0.0006745 | 0.7568659 | 0.7554715 | 0.0129007 |
| 217 | Complex-I-biogenesis | 54 | 0.0000000 | 0.5002449 | -0.5675026 | 0.0000000 | 0.0000000 | 0.7565079 | 0.7550116 | 0.0000000 |
| 1149 | Selenoamino-acid-metabolism | 91 | 0.0000000 | 0.4964672 | -0.5696762 | 0.0000000 | 0.0000000 | 0.7556525 | 0.7538772 | 0.0000000 |
| 1279 | Synthesis-of-PE | 12 | 0.0025219 | 0.5284326 | -0.5298587 | 0.0015235 | 0.0014787 | 0.7483256 | 0.7483250 | 0.0159720 |
| 198 | Citric-acid-cycle-(TCA-cycle) | 22 | 0.0000215 | 0.5010784 | -0.5421967 | 0.0000471 | 0.0000106 | 0.7382797 | 0.7377069 | 0.0003470 |
| 182 | Cellular-response-to-starvation | 138 | 0.0000000 | 0.5169261 | -0.5210817 | 0.0000000 | 0.0000000 | 0.7339882 | 0.7339824 | 0.0000000 |
| 277 | Defective-GALNT12-causes-colorectal-cancer-1-(CRCS1) | 12 | 0.0013492 | 0.6058398 | -0.4053232 | 0.0002783 | 0.0150319 | 0.7289230 | 0.7150002 | 0.0096597 |
| 1131 | STING-mediated-induction-of-host-immune-responses | 12 | 0.0033060 | -0.4586026 | 0.5524687 | 0.0059379 | 0.0009180 | 0.7180097 | 0.7149353 | 0.0199978 |
| 131 | CD22-mediated-BCR-regulation | 17 | 0.0003165 | -0.5545070 | 0.4473041 | 0.0000752 | 0.0014042 | 0.7124317 | 0.7083874 | 0.0029814 |
| 566 | Influenza-Viral-RNA-Transcription-and-Replication | 118 | 0.0000000 | 0.4887061 | -0.5160120 | 0.0000000 | 0.0000000 | 0.7107053 | 0.7104430 | 0.0000000 |
| 711 | Mitochondrial-tRNA-aminoacylation | 18 | 0.0003128 | -0.5263139 | 0.4683673 | 0.0001103 | 0.0005793 | 0.7045383 | 0.7033458 | 0.0029712 |
| 70 | Alpha-protein-kinase-1-signaling-pathway | 10 | 0.0087282 | 0.4270733 | -0.5589321 | 0.0193429 | 0.0022046 | 0.7034179 | 0.6972111 | 0.0426905 |
| 493 | Glutamate-and-glutamine-metabolism | 12 | 0.0049018 | 0.4628334 | -0.5246751 | 0.0054935 | 0.0016454 | 0.6996419 | 0.6982740 | 0.0272310 |
| 599 | Interleukin-2-signaling | 11 | 0.0089915 | -0.5178013 | 0.4508467 | 0.0029378 | 0.0096079 | 0.6865719 | 0.6849376 | 0.0436897 |
| 1093 | Respiratory-electron-transport | 99 | 0.0000000 | 0.4302327 | -0.5274937 | 0.0000000 | 0.0000000 | 0.6806980 | 0.6772148 | 0.0000000 |
| 552 | IRF3-mediated-induction-of-type-I-IFN | 10 | 0.0091500 | -0.3772082 | 0.5593936 | 0.0388522 | 0.0021861 | 0.6746905 | 0.6622775 | 0.0441704 |
| 1044 | Regulation-of-KIT-signaling | 16 | 0.0010631 | -0.4123908 | 0.5298141 | 0.0042834 | 0.0002424 | 0.6713935 | 0.6662395 | 0.0078776 |
| 1480 | tRNA-processing-in-the-mitochondrion | 16 | 0.0021235 | 0.4735060 | -0.4551834 | 0.0010384 | 0.0016157 | 0.6568103 | 0.6566826 | 0.0136235 |
| 111 | Basigin-interactions | 24 | 0.0000155 | 0.5533968 | -0.3507790 | 0.0000027 | 0.0029251 | 0.6552053 | 0.6393489 | 0.0002740 |
| 526 | HS-GAG-degradation | 20 | 0.0001790 | -0.3697386 | 0.5363698 | 0.0041945 | 0.0000327 | 0.6514593 | 0.6407154 | 0.0018173 |
| 1094 | Respiratory-electron-transport,-ATP-synthesis-by-chemiosmotic-coupling,-and-heat-production-by-uncoupling-proteins. | 107 | 0.0000000 | 0.4064936 | -0.4986485 | 0.0000000 | 0.0000000 | 0.6433408 | 0.6400321 | 0.0000000 |
| 116 | Bicarbonate-transporters | 10 | 0.0000011 | 0.6222025 | 0.1039584 | 0.0006552 | 0.5691401 | 0.6308275 | 0.3664539 | 0.0000336 |
| 565 | Influenza-Infection | 134 | 0.0000000 | 0.4225862 | -0.4537648 | 0.0000000 | 0.0000000 | 0.6200658 | 0.6196738 | 0.0000000 |
| 1067 | Regulation-of-expression-of-SLITs-and-ROBOs | 149 | 0.0000000 | 0.3794938 | -0.4750703 | 0.0000000 | 0.0000000 | 0.6080356 | 0.6042681 | 0.0000000 |
| 679 | Metabolism-of-Angiotensinogen-to-Angiotensins | 12 | 0.0200303 | 0.4147850 | -0.4390163 | 0.0128357 | 0.0084444 | 0.6039718 | 0.6037287 | 0.0822296 |
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## Output created: /tmp/RtmpjA4ug9/mitch_report.html## [1] TRUE# senescence
sen <- res$enrichment_result[grep("senescen",res$enrichment_result$set,ignore.case = TRUE),]
sen %>% kbl() %>% kable_paper("hover", full_width = F)| set | setSize | pMANOVA | s.diab | s.PMX | p.diab | p.PMX | s.dist | SD | p.adjustMANOVA | |
|---|---|---|---|---|---|---|---|---|---|---|
| 1155 | Senescence-Associated-Secretory-Phenotype-(SASP) | 48 | 0.0229467 | 0.2252022 | -0.1850079 | 0.0069282 | 0.0265307 | 0.2914514 | 0.2900623 | 0.0903303 |
| 427 | Formation-of-Senescence-Associated-Heterochromatin-Foci-(SAHF) | 11 | 0.7468897 | -0.0756495 | 0.1315434 | 0.6639360 | 0.4499285 | 0.1517448 | 0.1465074 | 0.8449546 |
| 824 | Oxidative-Stress-Induced-Senescence | 62 | 0.7860083 | -0.0488632 | 0.0229487 | 0.5056224 | 0.7545526 | 0.0539839 | 0.0507787 | 0.8745228 |
| 255 | DNA-Damage/Telomere-Stress-Induced-Senescence | 28 | 0.7740845 | 0.0099873 | 0.0496498 | 0.9271040 | 0.6492285 | 0.0506444 | 0.0280456 | 0.8638503 |
| 815 | Oncogene-Induced-Senescence | 31 | 0.7355955 | -0.0148105 | -0.0481470 | 0.8864896 | 0.6425978 | 0.0503734 | 0.0235725 | 0.8372907 |
| 177 | Cellular-Senescence | 124 | 0.9537872 | -0.0037689 | -0.0087449 | 0.9421785 | 0.8663480 | 0.0095225 | 0.0035186 | 0.9680609 |
dim(sen)## [1] 6 10# cell cycle
cc <- res$enrichment_result[grep("cell-",res$enrichment_result$set,ignore.case = TRUE),]
cc %>% kbl() %>% kable_paper("hover", full_width = F)| set | setSize | pMANOVA | s.diab | s.PMX | p.diab | p.PMX | s.dist | SD | p.adjustMANOVA | |
|---|---|---|---|---|---|---|---|---|---|---|
| 80 | Antigen-activates-B-Cell-Receptor-(BCR)-leading-to-generation-of-second-messengers | 42 | 0.0040520 | -0.2791272 | 0.2626308 | 0.0017415 | 0.0032178 | 0.3832584 | 0.3830808 | 0.0233663 |
| 86 | Apoptotic-cleavage-of-cell-adhesion–proteins | 10 | 0.0609162 | 0.3434820 | -0.0441210 | 0.0599667 | 0.8090716 | 0.3463041 | 0.2740767 | 0.1739458 |
| 18 | APC:Cdc20-mediated-degradation-of-cell-cycle-proteins-prior-to-satisfation-of-the-cell-cycle-checkpoint | 71 | 0.0000341 | 0.1502713 | -0.3014511 | 0.0284917 | 0.0000111 | 0.3368297 | 0.3194160 | 0.0004871 |
| 1320 | TP53-Regulates-Transcription-of-Genes-Involved-in-G2-Cell-Cycle-Arrest | 18 | 0.0347393 | 0.3151515 | -0.1000039 | 0.0206002 | 0.4625448 | 0.3306377 | 0.2935592 | 0.1234621 |
| 359 | ERBB2-Regulates-Cell-Motility | 14 | 0.0613171 | 0.0805283 | -0.3144161 | 0.6018439 | 0.0416231 | 0.3245648 | 0.2792679 | 0.1747538 |
| 408 | FOXO-mediated-transcription-of-cell-cycle-genes | 15 | 0.2624920 | 0.2357017 | -0.2069784 | 0.1139383 | 0.1650938 | 0.3136803 | 0.3130221 | 0.4405585 |
| 13 | APC/C-mediated-degradation-of-cell-cycle-proteins | 85 | 0.0000682 | 0.1517125 | -0.2707608 | 0.0155588 | 0.0000157 | 0.3103676 | 0.2987337 | 0.0008286 |
| 1077 | Regulation-of-mitotic-cell-cycle | 85 | 0.0000682 | 0.1517125 | -0.2707608 | 0.0155588 | 0.0000157 | 0.3103676 | 0.2987337 | 0.0008286 |
| 1078 | Regulation-of-necroptotic-cell-death | 26 | 0.0572414 | 0.1325825 | -0.2630009 | 0.2418396 | 0.0202406 | 0.2945294 | 0.2797196 | 0.1682956 |
| 338 | Downstream-signaling-events-of-B-Cell-Receptor-(BCR) | 79 | 0.0000033 | 0.0476953 | -0.2682978 | 0.4634198 | 0.0000370 | 0.2725042 | 0.2234408 | 0.0000874 |
| 1065 | Regulation-of-beta-cell-development | 35 | 0.1036214 | -0.2014802 | 0.1753504 | 0.0390807 | 0.0725285 | 0.2670993 | 0.2664595 | 0.2442248 |
| 581 | Integrin-cell-surface-interactions | 64 | 0.0007604 | -0.0696789 | 0.2407191 | 0.3348441 | 0.0008619 | 0.2506010 | 0.2194846 | 0.0060520 |
| 27 | Aberrant-regulation-of-mitotic-cell-cycle-due-to-RB1-defects | 36 | 0.0721409 | 0.2170007 | -0.1188437 | 0.0242100 | 0.2170843 | 0.2474129 | 0.2374779 | 0.1938210 |
| 1319 | TP53-Regulates-Transcription-of-Genes-Involved-in-G1-Cell-Cycle-Arrest | 13 | 0.3668777 | 0.2191673 | -0.1074301 | 0.1711884 | 0.5023700 | 0.2440810 | 0.2309392 | 0.5426274 |
| 323 | Diseases-of-mitotic-cell-cycle | 38 | 0.0752894 | 0.2101840 | -0.1180133 | 0.0249149 | 0.2079449 | 0.2410487 | 0.2320706 | 0.1979290 |
| 1424 | VEGFR2-mediated-cell-proliferation | 19 | 0.2806390 | 0.2059751 | -0.1068687 | 0.1200475 | 0.4199006 | 0.2320488 | 0.2212140 | 0.4589589 |
| 168 | Cell-Cycle-Checkpoints | 249 | 0.0000104 | 0.1533172 | -0.1680226 | 0.0000301 | 0.0000048 | 0.2274593 | 0.2272215 | 0.0001967 |
| 755 | NRIF-signals-cell-death-from-the-nucleus | 15 | 0.4664591 | 0.1221816 | -0.1840689 | 0.4125587 | 0.2170201 | 0.2209292 | 0.2165518 | 0.6371358 |
| 1315 | TP53-Regulates-Transcription-of-Cell-Cycle-Genes | 46 | 0.0469361 | 0.1989688 | -0.0856057 | 0.0195152 | 0.3149678 | 0.2166032 | 0.2012246 | 0.1467497 |
| 1153 | Sema4D-induced-cell-migration-and-growth-cone-collapse | 19 | 0.1522459 | 0.2110366 | -0.0374247 | 0.1112102 | 0.7775891 | 0.2143293 | 0.1756887 | 0.3146840 |
| 759 | Nef-mediates-down-modulation-of-cell-surface-receptors-by-recruiting-them-to-clathrin-adapters | 20 | 0.0869923 | 0.0299524 | 0.1864088 | 0.8165953 | 0.1488890 | 0.1887999 | 0.1106314 | 0.2151091 |
| 665 | MET-promotes-cell-motility | 29 | 0.2297951 | -0.0701035 | 0.1719703 | 0.5134062 | 0.1088721 | 0.1857103 | 0.1711721 | 0.4059075 |
| 409 | FOXO-mediated-transcription-of-cell-death-genes | 15 | 0.7171385 | -0.0906935 | 0.1211211 | 0.5430380 | 0.4166117 | 0.1513130 | 0.1497755 | 0.8238754 |
| 176 | Cell-extracellular-matrix-interactions | 16 | 0.2043060 | -0.1323725 | -0.0702542 | 0.3592250 | 0.6265343 | 0.1498604 | 0.0439243 | 0.3770629 |
| 95 | Assembly-and-cell-surface-presentation-of-NMDA-receptors | 25 | 0.0982708 | 0.1220062 | 0.0745967 | 0.2909053 | 0.5184362 | 0.1430041 | 0.0335236 | 0.2359079 |
| 169 | Cell-Cycle,-Mitotic | 479 | 0.0000944 | 0.1141548 | -0.0849284 | 0.0000178 | 0.0014113 | 0.1422819 | 0.1407731 | 0.0010762 |
| 171 | Cell-junction-organization | 78 | 0.2166522 | 0.1143010 | -0.0830477 | 0.0807968 | 0.2045566 | 0.1412857 | 0.1395466 | 0.3891862 |
| 167 | Cell-Cycle | 603 | 0.0001233 | 0.1007879 | -0.0709600 | 0.0000222 | 0.0028271 | 0.1232621 | 0.1214442 | 0.0013441 |
| 173 | Cell-surface-interactions-at-the-vascular-wall | 126 | 0.0305363 | -0.0183701 | 0.1109317 | 0.7215760 | 0.0313915 | 0.1124425 | 0.0914302 | 0.1120168 |
| 1322 | TP53-regulates-transcription-of-several-additional-cell-death-genes-whose-specific-roles-in-p53-dependent-apoptosis-remain-uncertain | 13 | 0.8641843 | 0.0767647 | -0.0816698 | 0.6317382 | 0.6101046 | 0.1120838 | 0.1120301 | 0.9270790 |
| 920 | Programmed-Cell-Death | 185 | 0.1236421 | 0.0682549 | -0.0861350 | 0.1089975 | 0.0431084 | 0.1098999 | 0.1091702 | 0.2738976 |
| 1254 | Signaling-by-the-B-Cell-Receptor-(BCR) | 120 | 0.0026570 | -0.0658351 | -0.0785462 | 0.2125894 | 0.1369622 | 0.1024879 | 0.0089882 | 0.0166852 |
| 175 | Cell-cell-junction-organization | 53 | 0.2737503 | 0.0970036 | -0.0057634 | 0.2216984 | 0.9421192 | 0.0971747 | 0.0726672 | 0.4527878 |
| 174 | Cell-Cell-communication | 110 | 0.2015524 | 0.0840235 | -0.0197332 | 0.1276586 | 0.7205071 | 0.0863097 | 0.0733671 | 0.3760791 |
| 172 | Cell-recruitment-(pro-inflammatory-response) | 24 | 0.8996479 | -0.0445363 | 0.0530312 | 0.7056241 | 0.6528508 | 0.0692517 | 0.0689907 | 0.9469305 |
| 1321 | TP53-regulates-transcription-of-additional-cell-cycle-genes-whose-exact-role-in-the-p53-pathway-remain-uncertain | 19 | 0.9331779 | 0.0487887 | -0.0384452 | 0.7127091 | 0.7716903 | 0.0621158 | 0.0616837 | 0.9575218 |
| 170 | Cell-death-signalling-via-NRAGE,-NRIF-and-NADE | 73 | 0.5410144 | 0.0489997 | 0.0078546 | 0.4689508 | 0.9075815 | 0.0496253 | 0.0290940 | 0.6905972 |
| 349 | EGR2-and-SOX10-mediated-initiation-of-Schwann-cell-myelination | 27 | 0.9344126 | -0.0397815 | 0.0201572 | 0.7204485 | 0.8561069 | 0.0445968 | 0.0423830 | 0.9576760 |
| 324 | Diseases-of-programmed-cell-death | 42 | 0.7998377 | -0.0435775 | 0.0001997 | 0.6249917 | 0.9982126 | 0.0435779 | 0.0309551 | 0.8865815 |
| 1316 | TP53-Regulates-Transcription-of-Cell-Death-Genes | 37 | 0.8402658 | 0.0054984 | 0.0368905 | 0.9538359 | 0.6977050 | 0.0372980 | 0.0221976 | 0.9076340 |
dim(cc)## [1] 40 10custom_sets <- genesets[union(grep("cell-",names(genesets),ignore.case = TRUE), grep("senescen",names(genesets),ignore.case = TRUE))]
length(custom_sets)## [1] 76res2 <- mitch_calc(m, custom_sets , priority = "effect",resrows = 100)## Note: Enrichments with large effect sizes may not be
## statistically significant.res2$enrichment_result %>% kbl() %>% kable_paper("hover", full_width = F)| set | setSize | pMANOVA | s.diab | s.PMX | p.diab | p.PMX | s.dist | SD | p.adjustMANOVA | |
|---|---|---|---|---|---|---|---|---|---|---|
| 4 | Antigen-activates-B-Cell-Receptor-(BCR)-leading-to-generation-of-second-messengers | 42 | 0.0040520 | -0.2791272 | 0.2626308 | 0.0017415 | 0.0032178 | 0.3832584 | 0.3830808 | 0.0186394 |
| 5 | Apoptotic-cleavage-of-cell-adhesion–proteins | 10 | 0.0609162 | 0.3434820 | -0.0441210 | 0.0599667 | 0.8090716 | 0.3463041 | 0.2740767 | 0.1659169 |
| 2 | APC:Cdc20-mediated-degradation-of-cell-cycle-proteins-prior-to-satisfation-of-the-cell-cycle-checkpoint | 71 | 0.0000341 | 0.1502713 | -0.3014511 | 0.0284917 | 0.0000111 | 0.3368297 | 0.3194160 | 0.0005230 |
| 37 | TP53-Regulates-Transcription-of-Genes-Involved-in-G2-Cell-Cycle-Arrest | 18 | 0.0347393 | 0.3151515 | -0.1000039 | 0.0206002 | 0.4625448 | 0.3306377 | 0.2935592 | 0.1229238 |
| 21 | ERBB2-Regulates-Cell-Motility | 14 | 0.0613171 | 0.0805283 | -0.3144161 | 0.6018439 | 0.0416231 | 0.3245648 | 0.2792679 | 0.1659169 |
| 22 | FOXO-mediated-transcription-of-cell-cycle-genes | 15 | 0.2624920 | 0.2357017 | -0.2069784 | 0.1139383 | 0.1650938 | 0.3136803 | 0.3130221 | 0.4163666 |
| 1 | APC/C-mediated-degradation-of-cell-cycle-proteins | 85 | 0.0000682 | 0.1517125 | -0.2707608 | 0.0155588 | 0.0000157 | 0.3103676 | 0.2987337 | 0.0006275 |
| 30 | Regulation-of-mitotic-cell-cycle | 85 | 0.0000682 | 0.1517125 | -0.2707608 | 0.0155588 | 0.0000157 | 0.3103676 | 0.2987337 | 0.0006275 |
| 31 | Regulation-of-necroptotic-cell-death | 26 | 0.0572414 | 0.1325825 | -0.2630009 | 0.2418396 | 0.0202406 | 0.2945294 | 0.2797196 | 0.1659169 |
| 46 | Senescence-Associated-Secretory-Phenotype-(SASP) | 48 | 0.0229467 | 0.2252022 | -0.1850079 | 0.0069282 | 0.0265307 | 0.2914514 | 0.2900623 | 0.0959590 |
| 19 | Downstream-signaling-events-of-B-Cell-Receptor-(BCR) | 79 | 0.0000033 | 0.0476953 | -0.2682978 | 0.4634198 | 0.0000370 | 0.2725042 | 0.2234408 | 0.0001518 |
| 29 | Regulation-of-beta-cell-development | 35 | 0.1036214 | -0.2014802 | 0.1753504 | 0.0390807 | 0.0725285 | 0.2670993 | 0.2664595 | 0.2166629 |
| 24 | Integrin-cell-surface-interactions | 64 | 0.0007604 | -0.0696789 | 0.2407191 | 0.3348441 | 0.0008619 | 0.2506010 | 0.2194846 | 0.0043723 |
| 3 | Aberrant-regulation-of-mitotic-cell-cycle-due-to-RB1-defects | 36 | 0.0721409 | 0.2170007 | -0.1188437 | 0.0242100 | 0.2170843 | 0.2474129 | 0.2374779 | 0.1822795 |
| 36 | TP53-Regulates-Transcription-of-Genes-Involved-in-G1-Cell-Cycle-Arrest | 13 | 0.3668777 | 0.2191673 | -0.1074301 | 0.1711884 | 0.5023700 | 0.2440810 | 0.2309392 | 0.5273866 |
| 17 | Diseases-of-mitotic-cell-cycle | 38 | 0.0752894 | 0.2101840 | -0.1180133 | 0.0249149 | 0.2079449 | 0.2410487 | 0.2320706 | 0.1822795 |
| 40 | VEGFR2-mediated-cell-proliferation | 19 | 0.2806390 | 0.2059751 | -0.1068687 | 0.1200475 | 0.4199006 | 0.2320488 | 0.2212140 | 0.4164320 |
| 8 | Cell-Cycle-Checkpoints | 249 | 0.0000104 | 0.1533172 | -0.1680226 | 0.0000301 | 0.0000048 | 0.2274593 | 0.2272215 | 0.0002381 |
| 26 | NRIF-signals-cell-death-from-the-nucleus | 15 | 0.4664591 | 0.1221816 | -0.1840689 | 0.4125587 | 0.2170201 | 0.2209292 | 0.2165518 | 0.6502156 |
| 34 | TP53-Regulates-Transcription-of-Cell-Cycle-Genes | 46 | 0.0469361 | 0.1989688 | -0.0856057 | 0.0195152 | 0.3149678 | 0.2166032 | 0.2012246 | 0.1542187 |
| 32 | Sema4D-induced-cell-migration-and-growth-cone-collapse | 19 | 0.1522459 | 0.2110366 | -0.0374247 | 0.1112102 | 0.7775891 | 0.2143293 | 0.1756887 | 0.2918047 |
| 27 | Nef-mediates-down-modulation-of-cell-surface-receptors-by-recruiting-them-to-clathrin-adapters | 20 | 0.0869923 | 0.0299524 | 0.1864088 | 0.8165953 | 0.1488890 | 0.1887999 | 0.1106314 | 0.2000822 |
| 25 | MET-promotes-cell-motility | 29 | 0.2297951 | -0.0701035 | 0.1719703 | 0.5134062 | 0.1088721 | 0.1857103 | 0.1711721 | 0.3775206 |
| 43 | Formation-of-Senescence-Associated-Heterochromatin-Foci-(SAHF) | 11 | 0.7468897 | -0.0756495 | 0.1315434 | 0.6639360 | 0.4499285 | 0.1517448 | 0.1465074 | 0.9198134 |
| 23 | FOXO-mediated-transcription-of-cell-death-genes | 15 | 0.7171385 | -0.0906935 | 0.1211211 | 0.5430380 | 0.4166117 | 0.1513130 | 0.1497755 | 0.9198134 |
| 16 | Cell-extracellular-matrix-interactions | 16 | 0.2043060 | -0.1323725 | -0.0702542 | 0.3592250 | 0.6265343 | 0.1498604 | 0.0439243 | 0.3614645 |
| 6 | Assembly-and-cell-surface-presentation-of-NMDA-receptors | 25 | 0.0982708 | 0.1220062 | 0.0745967 | 0.2909053 | 0.5184362 | 0.1430041 | 0.0335236 | 0.2152598 |
| 9 | Cell-Cycle,-Mitotic | 479 | 0.0000944 | 0.1141548 | -0.0849284 | 0.0000178 | 0.0014113 | 0.1422819 | 0.1407731 | 0.0007238 |
| 11 | Cell-junction-organization | 78 | 0.2166522 | 0.1143010 | -0.0830477 | 0.0807968 | 0.2045566 | 0.1412857 | 0.1395466 | 0.3691112 |
| 7 | Cell-Cycle | 603 | 0.0001233 | 0.1007879 | -0.0709600 | 0.0000222 | 0.0028271 | 0.1232621 | 0.1214442 | 0.0008105 |
| 13 | Cell-surface-interactions-at-the-vascular-wall | 126 | 0.0305363 | -0.0183701 | 0.1109317 | 0.7215760 | 0.0313915 | 0.1124425 | 0.0914302 | 0.1170558 |
| 39 | TP53-regulates-transcription-of-several-additional-cell-death-genes-whose-specific-roles-in-p53-dependent-apoptosis-remain-uncertain | 13 | 0.8641843 | 0.0767647 | -0.0816698 | 0.6317382 | 0.6101046 | 0.1120838 | 0.1120301 | 0.9464875 |
| 28 | Programmed-Cell-Death | 185 | 0.1236421 | 0.0682549 | -0.0861350 | 0.1089975 | 0.0431084 | 0.1098999 | 0.1091702 | 0.2472841 |
| 33 | Signaling-by-the-B-Cell-Receptor-(BCR) | 120 | 0.0026570 | -0.0658351 | -0.0785462 | 0.2125894 | 0.1369622 | 0.1024879 | 0.0089882 | 0.0135803 |
| 15 | Cell-cell-junction-organization | 53 | 0.2737503 | 0.0970036 | -0.0057634 | 0.2216984 | 0.9421192 | 0.0971747 | 0.0726672 | 0.4164320 |
| 14 | Cell-Cell-communication | 110 | 0.2015524 | 0.0840235 | -0.0197332 | 0.1276586 | 0.7205071 | 0.0863097 | 0.0733671 | 0.3614645 |
| 12 | Cell-recruitment-(pro-inflammatory-response) | 24 | 0.8996479 | -0.0445363 | 0.0530312 | 0.7056241 | 0.6528508 | 0.0692517 | 0.0689907 | 0.9537872 |
| 38 | TP53-regulates-transcription-of-additional-cell-cycle-genes-whose-exact-role-in-the-p53-pathway-remain-uncertain | 19 | 0.9331779 | 0.0487887 | -0.0384452 | 0.7127091 | 0.7716903 | 0.0621158 | 0.0616837 | 0.9537872 |
| 45 | Oxidative-Stress-Induced-Senescence | 62 | 0.7860083 | -0.0488632 | 0.0229487 | 0.5056224 | 0.7545526 | 0.0539839 | 0.0507787 | 0.9198134 |
| 42 | DNA-Damage/Telomere-Stress-Induced-Senescence | 28 | 0.7740845 | 0.0099873 | 0.0496498 | 0.9271040 | 0.6492285 | 0.0506444 | 0.0280456 | 0.9198134 |
| 44 | Oncogene-Induced-Senescence | 31 | 0.7355955 | -0.0148105 | -0.0481470 | 0.8864896 | 0.6425978 | 0.0503734 | 0.0235725 | 0.9198134 |
| 10 | Cell-death-signalling-via-NRAGE,-NRIF-and-NADE | 73 | 0.5410144 | 0.0489997 | 0.0078546 | 0.4689508 | 0.9075815 | 0.0496253 | 0.0290940 | 0.7319607 |
| 20 | EGR2-and-SOX10-mediated-initiation-of-Schwann-cell-myelination | 27 | 0.9344126 | -0.0397815 | 0.0201572 | 0.7204485 | 0.8561069 | 0.0445968 | 0.0423830 | 0.9537872 |
| 18 | Diseases-of-programmed-cell-death | 42 | 0.7998377 | -0.0435775 | 0.0001997 | 0.6249917 | 0.9982126 | 0.0435779 | 0.0309551 | 0.9198134 |
| 35 | TP53-Regulates-Transcription-of-Cell-Death-Genes | 37 | 0.8402658 | 0.0054984 | 0.0368905 | 0.9538359 | 0.6977050 | 0.0372980 | 0.0221976 | 0.9427372 |
| 41 | Cellular-Senescence | 124 | 0.9537872 | -0.0037689 | -0.0087449 | 0.9421785 | 0.8663480 | 0.0095225 | 0.0035186 | 0.9537872 |
mitch_report(res2,outfile = "pmx_cell_senescence_report.html")## Dataset saved as " /tmp/RtmpjA4ug9/pmx_cell_senescence_report.rds ".##
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## label: detailed_geneset_reports2d (with options)
## List of 7
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## label: session_info (with options)
## List of 3
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## $ echo : logi TRUE
## $ results: chr "markup"
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## ordinary text without R code## output file: /home/mdz/projects/pmx53/mitch.knit.md## /usr/bin/pandoc +RTS -K512m -RTS /home/mdz/projects/pmx53/mitch.knit.md --to html4 --from markdown+autolink_bare_uris+tex_math_single_backslash --output /tmp/RtmpjA4ug9/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/RtmpjA4ug9/rmarkdown-str132eb520df28d0.html##
## Output created: /tmp/RtmpjA4ug9/mitch_report.html## [1] TRUEFor reproducibility
sessionInfo()## R version 4.2.1 (2022-06-23)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.1 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] pkgload_1.3.2 GGally_2.1.2
## [3] ggplot2_3.4.0 reshape2_1.4.4
## [5] beeswarm_0.4.0 gplots_3.1.3
## [7] gtools_3.9.4 tibble_3.1.8
## [9] echarts4r_0.4.4 kableExtra_1.3.4
## [11] dplyr_1.0.10 mitch_1.11.1
## [13] DESeq2_1.36.0 SummarizedExperiment_1.26.1
## [15] Biobase_2.56.0 MatrixGenerics_1.8.1
## [17] matrixStats_0.63.0 GenomicRanges_1.48.0
## [19] GenomeInfoDb_1.32.4 IRanges_2.30.1
## [21] S4Vectors_0.34.0 BiocGenerics_0.42.0
##
## loaded via a namespace (and not attached):
## [1] colorspace_2.0-3 ellipsis_0.3.2 XVector_0.36.0
## [4] rstudioapi_0.14 farver_2.1.1 bit64_4.0.5
## [7] AnnotationDbi_1.58.0 fansi_1.0.3 xml2_1.3.3
## [10] codetools_0.2-18 splines_4.2.1 cachem_1.0.6
## [13] geneplotter_1.74.0 knitr_1.41 jsonlite_1.8.3
## [16] annotate_1.74.0 png_0.1-8 shiny_1.7.3
## [19] compiler_4.2.1 httr_1.4.4 assertthat_0.2.1
## [22] Matrix_1.5-3 fastmap_1.1.0 cli_3.4.1
## [25] later_1.3.0 htmltools_0.5.3 tools_4.2.1
## [28] gtable_0.3.1 glue_1.6.2 GenomeInfoDbData_1.2.8
## [31] Rcpp_1.0.9 jquerylib_0.1.4 vctrs_0.5.1
## [34] Biostrings_2.64.1 svglite_2.1.0 xfun_0.35
## [37] stringr_1.4.1 rvest_1.0.3 mime_0.12
## [40] lifecycle_1.0.3 XML_3.99-0.12 zlibbioc_1.42.0
## [43] MASS_7.3-58.1 scales_1.2.1 promises_1.2.0.1
## [46] parallel_4.2.1 RColorBrewer_1.1-3 yaml_2.3.6
## [49] memoise_2.0.1 gridExtra_2.3 sass_0.4.4
## [52] reshape_0.8.9 stringi_1.7.8 RSQLite_2.2.19
## [55] highr_0.9 genefilter_1.78.0 caTools_1.18.2
## [58] BiocParallel_1.30.4 rlang_1.0.6 pkgconfig_2.0.3
## [61] systemfonts_1.0.4 bitops_1.0-7 evaluate_0.18
## [64] lattice_0.20-45 htmlwidgets_1.5.4 labeling_0.4.2
## [67] bit_4.0.5 tidyselect_1.2.0 plyr_1.8.8
## [70] magrittr_2.0.3 R6_2.5.1 generics_0.1.3
## [73] DelayedArray_0.22.0 DBI_1.1.3 pillar_1.8.1
## [76] withr_2.5.0 survival_3.4-0 KEGGREST_1.36.3
## [79] RCurl_1.98-1.9 crayon_1.5.2 KernSmooth_2.23-20
## [82] utf8_1.2.2 rmarkdown_2.18 locfit_1.5-9.6
## [85] grid_4.2.1 blob_1.2.3 digest_0.6.30
## [88] webshot_0.5.4 xtable_1.8-4 httpuv_1.6.6
## [91] munsell_0.5.0 viridisLite_0.4.1 bslib_0.4.1