DataPrep
Cas Baptist
3/7/2022
Introduction
set org = the organism you wish to test
The heirarchical clustering step needs a larger stack. Run this before executing:
ulimit -s 65533
Prerequisite libraries
suppressPackageStartupMessages({
library(R.utils)
library(dplyr)
library(tidyr)
library(data.table)
library(RColorBrewer)
library(gplots)
library(edgeR)
library(reshape2)
library(Polychrome)
library(dendextend)
library(ggplot2)
library(DESeq2)
library(dynamicTreeCut)
library(biomaRt)
library(qdapTools)
})
source("functions.R")1. Download and unzip the Human data
# if statement checks if object exists
if ( !dir.exists("Data")) { dir.create("Data") }
if (!file.exists("Data/hsapiens_rand_se.tsv.bz2")){
download.file("http://ziemann-lab.net/public/cas/rand/hsapiens_rand_se.tsv.bz2",
destfile = "Data/hsapiens_rand_se.tsv.bz2")}
if (!file.exists("Data/hsapiens_rand_se.tsv")){
bunzip2("Data/hsapiens_rand_se.tsv.bz2", destname="Data/hsapiens_rand_se.tsv")}
orgData <- fread("Data/hsapiens_rand_se.tsv", sep = '\t', header = FALSE)
head(orgData)## V1 V2 V3
## 1: DRR008995 ENSG00000223972 0
## 2: DRR008995 ENSG00000227232 0
## 3: DRR008995 ENSG00000278267 0
## 4: DRR008995 ENSG00000243485 0
## 5: DRR008995 ENSG00000284332 0
## 6: DRR008995 ENSG00000237613 02. Download, read, and unzip the QC data
if (!file.exists("hsapiens_rand_qc.tsv.bz2")){
download.file("http://ziemann-lab.net/public/cas/rand/hsapiens_rand_qc.tsv.bz2",
destfile = "hsapiens_rand_qc.tsv.bz2")}
qcData <- fread("hsapiens_rand_qc.tsv.bz2", sep = '\t',
col.names = c("Database", "Description", "Details"))
head(qcData)## Database Description Details
## 1: DRR008995 QualityEncoding Sanger/Illumina1.9
## 2: DRR008995 Read1MinimumLength 7
## 3: DRR008995 Read1MedianLength 26
## 4: DRR008995 Read1MaxLength 120
## 5: DRR008995 Read2MinimumLength NULL
## 6: DRR008995 Read2MedianLength NULL3. Filter and quantify databases according to qcSummary = PASS, WARN, or FAIL.
# Count the total number of qcSummary entries for checking
qcSummary <- qcData[qcData$Description == 'qcSummary',]
totalSummary <- nrow(qcSummary)
# Count the total number of databases marked as PASS
qcPass <- filter(qcData, grepl("PASS", Details))
totalPass <- nrow(qcPass)
# Count the total number of databases marked as WARN
qcWarn <- filter(qcData, grepl("WARN", Details))
totalWarn <- nrow(qcWarn)
# Count the total number of databases marked as FAIL
qcFail <- filter(qcData, grepl("FAIL", Details))
totalFail <- nrow(qcFail)
# Summary of counts. Addition of each PASS, WARN, and FAIL counts equals to total_summary.
qualitySummary <- data.frame(totalPass, totalWarn, totalFail, totalSummary)
qualitySummary## totalPass totalWarn totalFail totalSummary
## 1 197 310 604 04. Select all the databases from org_se.tsv with qcSummary == ‘PASS’
# Filter all the sample names with qcSummary == 'PASS' from step 3
databasePass <- filter(qcData, grepl("PASS", Details))
# Convert the rows into string and store on a list to use for filtering org data
databasePassList <- as.character(databasePass$Database)
str(databasePassList)## chr [1:197] "DRR017573" "DRR108715" "DRR109691" "DRR109692" "ERR1518673" ...# Filter org data using generated list
orgPass <- orgData[orgData$V1 %in% databasePassList,]
# Convert format from long to wide
orgPassWide <- orgPass %>% pivot_wider(names_from = "V1", values_from = "V3")
# Convert tibble to data frame and assign column 1 as rowname
orgPassWide <- as.data.frame(orgPassWide)
rownames(orgPassWide) <- orgPassWide[,1]
orgPassWide <- orgPassWide[,-1]
orgPassWide[1:10,1:6]## DRR017573 DRR108715 DRR109691 DRR109692 ERR1518673 ERR1594743
## ENSG00000223972 1 0 0 0 0 0
## ENSG00000227232 0 0 0 0 12 20
## ENSG00000278267 0 0 0 0 2 1
## ENSG00000243485 0 0 0 0 1 0
## ENSG00000284332 0 0 0 0 0 0
## ENSG00000237613 0 0 0 0 0 0
## ENSG00000268020 0 0 0 0 0 0
## ENSG00000240361 0 0 0 0 0 1
## ENSG00000186092 0 0 0 0 0 0
## ENSG00000238009 6 0 0 0 0 1saveRDS(orgPassWide, "orgPassWide.rds")
# Remove unneeded data
remove(orgPass)
remove(databasePass)
remove(qcSummary)
remove(totalSummary)
remove(qcWarn)
remove(totalWarn)
remove(qcFail)
remove(totalFail)5. Aggregate multiple runs, if any, (SRR) to its corresponding experiment (SRX) with PASS only databases
# Download and read Metadata summary
if (!file.exists("hsapiens_metadata.tsv.cut")){
download.file("http://ziemann-lab.net/public/cas/rand/hsapiens_metadata.tsv.cut",
destfile = "hsapiens_metadata.tsv.cut")}
orgMetadata <- read.csv("hsapiens_metadata.tsv.cut", sep = '\t')
# Filter metadata to include only "passed" samples
orgMetadataPass <- orgMetadata[which(orgMetadata$SRR_accession %in% databasePassList),]
# Assign column 1 as rownames
rownames(orgMetadataPass) <- orgMetadataPass[,1]
orgMetadataPass <- orgMetadataPass[,-1]
orgMetadataPass## QC_summary SRX_accession SRS_accession SRP_accession
## DRR017573 PASS DRX015849 DRS015339 DRP001953
## DRR108715 PASS DRX101804 DRS110100 DRP005525
## DRR109691 PASS DRX102780 DRS111076 DRP005525
## DRR109692 PASS DRX102781 DRS111077 DRP005525
## ERR1518673 PASS ERX1589652 ERS1236828 ERP012979
## ERR1594743 PASS ERX1665329 ERS1461229 ERP007111
## ERR1691932 PASS ERX1761560 ERS1413850 ERP017989
## ERR188129 PASS ERX163089 ERS185054 ERP001942
## ERR188184 PASS ERX162902 ERS185087 ERP001942
## ERR1910862 PASS ERX1971342 ERS1645519 ERP022368
## ERR1991839 PASS ERX2051727 ERS2004882 ERP022909
## ERR204924 PASS ERX179574 ERS185387 ERP001942
## ERR2059979 PASS ERX2119036 ERS1847632 ERP024173
## ERR2208954 PASS ERX2263312 ERS2029078 ERP105482
## ERR2303756 PASS ERX2355092 ERS2202179 ERP106849
## ERR2445954 PASS ERX2465055 ERS2319707 ERP107676
## ERR2619180 PASS ERX2636877 ERS2537965 ERP109267
## ERR2675483 PASS ERX2690581 ERS2586517 ERP109626
## ERR2700003 PASS ERX2714390 ERS2611382 ERP109918
## ERR3129937 PASS ERX3159179 ERS3087609 ERP110841
## ERR315411 PASS ERX288566 ERS326969 ERP003613
## ERR315466 PASS ERX288542 ERS326982 ERP003613
## ERR3299306 PASS ERX3325584 ERS3387401 ERP115010
## ERR3357674 PASS ERX3382181 ERS3496984 ERP115637
## ERR3490878 PASS ERX3512278 ERS3672302 ERP115010
## ERR576280 PASS ERX534692 ERS518723 ERP006577
## ERR752766 PASS ERX696448 ERS653509 ERP009437
## ERR752810 PASS ERX696492 ERS653523 ERP009437
## ERR866160 PASS ERX945788 ERS626270 ERP008967
## ERR973735 PASS ERX1050718 ERS801801 ERP011233
## SRR10009502 PASS SRX6747727 SRS5297959 SRP218977
## SRR10068994 PASS SRX6802628 SRS5347217 SRP220372
## SRR10118992 PASS SRX6848484 SRS5387029 SRP221604
## SRR10143223 PASS SRX6871148 SRS5407179 SRP222478
## SRR10181297 PASS SRX6902647 SRS5434544 SRP223239
## SRR10259233 PASS SRX6977105 SRS5496382 SRP225086
## SRR10272816 PASS SRX6986027 SRS5509216 SRP225441
## SRR10353659 PASS SRX7063371 SRS5580115 SRP227161
## SRR10368246 PASS SRX7076240 SRS5592125 SRP227534
## SRR10446446 PASS SRX7141157 SRS5649298 SRP229963
## SRR10486655 PASS SRX7175968 SRS5682849 SRP230422
## SRR10505583 PASS SRX7194439 SRS5700376 SRP230868
## SRR10581909 PASS SRX7262339 SRS5757898 SRP234536
## SRR10582374 PASS SRX7262734 SRS5758291 SRP234568
## SRR10604806 PASS SRX7284285 SRS5777960 SRP235049
## SRR10620267 PASS SRX7299361 SRS5792599 SRP235561
## SRR10721014 PASS SRX7397669 SRS5845447 SRP237940
## SRR10741154 PASS SRX7416696 SRS5863503 SRP238240
## SRR10858280 PASS SRX7528404 SRS5967752 SRP240916
## SRR10858283 PASS SRX7528407 SRS5967755 SRP240916
## SRR11058878 PASS SRX7704819 SRS6128723 SRP248023
## SRR11058925 PASS SRX7704863 SRS6128767 SRP248025
## SRR11247856 PASS SRX7858323 SRS6267402 SRP251766
## SRR11247857 PASS SRX7858323 SRS6267402 SRP251766
## SRR11252261 PASS SRX7862381 SRS6271227 SRP251874
## SRR11290620 PASS SRX7896200 SRS6304765 SRP252428
## SRR11307901 PASS SRX7912999 SRS6319939 SRP223274
## SRR1146231 PASS SRX451455 SRS544667 SRP035988
## SRR11469900 PASS SRX8046405 SRS6417876 SRP254985
## SRR11470749 PASS SRX8047188 SRS6418628 SRP255013
## SRR11542124 PASS SRX8112222 SRS6477308 SRP256329
## SRR11547440 PASS SRX8117425 SRS6482351 SRP256409
## SRR11548469 PASS SRX8118494 SRS6483205 SRP256445
## SRR11586961 PASS SRX8154512 SRS6516808 SRP257863
## SRR11615379 PASS SRX8181746 SRS6540815 SRP258718
## SRR11652607 PASS SRX8213646 SRS6572874 SRP259314
## SRR11780588 PASS SRX8333139 SRS6652542 SRP261333
## SRR11869905 PASS SRX8419901 SRS6731427 SRP265176
## SRR1205933 PASS SRX501751 SRS582803 SRP040547
## SRR1272187 PASS SRX533781 SRS602509 SRP041706
## SRR1296129 PASS SRX550560 SRS618302 SRP042186
## SRR1448791 PASS SRX620751 SRS645155 SRP043510
## SRR1554437 PASS SRX683722 SRS686890 SRP045632
## SRR1576497 PASS SRX702197 SRS702061 SRP047194
## SRR1644195 PASS SRX753525 SRS738884 SRP049607
## SRR1702804 PASS SRX803956 SRS785863 SRP051039
## SRR1747214 PASS SRX834804 SRS812794 SRP051848
## SRR1777877 PASS SRX857514 SRS829464 SRP052896
## SRR1947537 PASS SRX974107 SRS889297 SRP056733
## SRR2063343 PASS SRX1059116 SRS961371 SRP059509
## SRR2099867 PASS SRX1094558 SRS989980 SRP061037
## SRR2156107 PASS SRX1143101 SRS1029380 SRP062278
## SRR2313080 PASS SRX1210926 SRS1060813 SRP063493
## SRR2422379 PASS SRX1250328 SRS1071360 SRP063851
## SRR2481165 PASS SRX1272402 SRS1079518 SRP063980
## SRR2506915 PASS SRX1282716 SRS1089571 SRP064138
## SRR2761447 PASS SRX1366803 SRS1128611 SRP065120
## SRR2970383 PASS SRX1459612 SRS1187057 SRP066917
## SRR3070185 PASS SRX1510918 SRS1230774 SRP062130
## SRR3192422 PASS SRX1603406 SRS1312897 SRP013565
## SRR3213396 PASS SRX1620842 SRS1329623 SRP071331
## SRR3234008 PASS SRX1639653 SRS1346263 SRP071932
## SRR3362723 PASS SRX1693989 SRS1395130 SRP073191
## SRR3408051 PASS SRX1717157 SRS1405935 SRP073667
## SRR3471776 PASS SRX1739134 SRS1419340 SRP074274
## SRR3471926 PASS SRX1739284 SRS1419490 SRP074274
## SRR3503567 PASS SRX1761117 SRS1436886 SRP075117
## SRR3538912 PASS SRX1770950 SRS1443235 SRP075319
## SRR3644744 PASS SRX1828952 SRS1490523 SRP076235
## SRR3714679 PASS SRX1874075 SRS1523921 SRP077046
## SRR3885719 PASS SRX1940990 SRS1559775 SRP078417
## SRR3930018 PASS SRX1959652 SRS1569757 SRP078912
## SRR3932740 PASS SRX1962063 SRS1571967 SRP078990
## SRR3944326 PASS SRX1970316 SRS1579373 SRP079342
## SRR3954218 PASS SRX1978468 SRS1586017 SRP079926
## SRR3987797 PASS SRX1989824 SRS1593654 SRP080367
## SRR4007767 PASS SRX2006122 SRS1605070 SRP078945
## SRR4113665 PASS SRX2086813 SRS1663028 SRP083954
## SRR4175280 PASS SRX2140530 SRS1661888 SRP083924
## SRR4240867 PASS SRX2161836 SRS1689988 SRP089788
## SRR4241352 PASS SRX2162324 SRS1690381 SRP089814
## SRR4255751 PASS SRX2175516 SRS1702804 SRP090124
## SRR4421980 PASS SRX2244269 SRS1745028 SRP013565
## SRR4428773 PASS SRX2250297 SRS1750267 SRP091695
## SRR5032377 PASS SRX2357303 SRS1806120 SRP093793
## SRR5104192 PASS SRX2420094 SRS1857412 SRP095037
## SRR5118039 PASS SRX2270678 SRS1761491 SRP092132
## SRR5124441 PASS SRX2439426 SRS1874042 SRP095491
## SRR5163544 PASS SRX2480703 SRS1912325 SRP096338
## SRR5185077 PASS SRX2501099 SRS1927481 SRP096982
## SRR5225467 PASS SRX2534583 SRS1955185 SRP098758
## SRR5225669 PASS SRX2534785 SRS1955387 SRP098758
## SRR5225767 PASS SRX2534883 SRS1955484 SRP098761
## SRR5236578 PASS SRX2543640 SRS1962707 SRP097611
## SRR5279123 PASS SRX2582949 SRS1996925 SRP100570
## SRR5305397 PASS SRX2606829 SRS2018106 SRP100947
## SRR5352626 PASS SRX2648853 SRS2054064 SRP102077
## SRR5352799 PASS SRX2649026 SRS2054236 SRP102077
## SRR542392 PASS SRX176430 SRS356035 SRP014830
## SRR5444892 PASS SRX2733947 SRS2121843 SRP103828
## SRR5445642 PASS SRX2734637 SRS2122503 SRP103864
## SRR5488704 PASS SRX2771550 SRS2154964 SRP105769
## SRR5495045 PASS SRX2776002 SRS2159290 SRP106049
## SRR5528039 PASS SRX2797234 SRS2178204 SRP106875
## SRR5553974 PASS SRX2819432 SRS2197584 SRP107025
## SRR5559252 PASS SRX2822371 SRS2199454 SRP107072
## SRR5676576 PASS SRX2912081 SRS2278368 SRP109030
## SRR5676577 PASS SRX2912081 SRS2278368 SRP109030
## SRR5750779 PASS SRX2951000 SRS2309424 SRP110289
## SRR5800692 PASS SRX2980159 SRS2333375 SRP110994
## SRR5802878 PASS SRX2982219 SRS2335278 SRP111061
## SRR5838317 PASS SRX3014615 SRS2364367 SRP112756
## SRR5862115 PASS SRX3030761 SRS2379649 SRP113470
## SRR5882130 PASS SRX3048805 SRS2395581 SRP114315
## SRR5901932 PASS SRX3063498 SRS2408888 SRP114871
## SRR5902186 PASS SRX3063752 SRS2408638 SRP114871
## SRR5934783 PASS SRX3094923 SRS2432096 SRP115470
## SRR5981038 PASS SRX3137041 SRS2469919 SRP116272
## SRR5999449 PASS SRX3154924 SRS2486760 SRP116913
## SRR6000438 PASS SRX3155896 SRS2487529 SRP116955
## SRR6036044 PASS SRX3184884 SRS2513325 SRP117629
## SRR6050275 PASS SRX3197275 SRS2524358 SRP118077
## SRR6066217 PASS SRX3209589 SRS2534582 SRP118760
## SRR6149831 PASS SRX3261849 SRS2575034 SRP119607
## SRR6217804 PASS SRX3326445 SRS2630194 SRP121472
## SRR6217826 PASS SRX3326455 SRS2630204 SRP121474
## SRR6233791 PASS SRX3342181 SRS2643587 SRP094756
## SRR6302566 PASS SRX3403476 SRS2706058 SRP125179
## SRR6337805 PASS SRX3436821 SRS2727765 SRP125961
## SRR6355995 PASS SRX3452604 SRS1802847 SRP126289
## SRR6369983 PASS SRX3465310 SRS2753257 SRP126582
## SRR6371359 PASS SRX3466682 SRS2754459 SRP126635
## SRR6464796 PASS SRX3554769 SRS2828122 SRP128927
## SRR6464797 PASS SRX3554769 SRS2828122 SRP128927
## SRR6464798 PASS SRX3554769 SRS2828122 SRP128927
## SRR6467601 PASS SRX3557548 SRS2830833 SRP129004
## SRR6467717 PASS SRX3557664 SRS2830946 SRP129004
## SRR6496863 PASS SRX3586008 SRS2854725 SRP131037
## SRR6503280 PASS SRX3591907 SRS2859986 SRP131149
## SRR6883165 PASS SRX3835409 SRS3082806 SRP136311
## SRR6926574 PASS SRX3872639 SRS3114043 SRP136938
## SRR6973585 PASS SRX3915416 SRS3151051 SRP139092
## SRR6978432 PASS SRX3919215 SRS3154204 SRP139334
## SRR7010505 PASS SRX3942984 SRS3173544 SRP140531
## SRR7011833 PASS SRX3944297 SRS3174833 SRP140558
## SRR7123448 PASS SRX4044517 SRS3261937 SRP144647
## SRR7130991 PASS SRX4051988 SRS3269027 SRP144905
## SRR7142047 PASS SRX4062867 SRS3279158 SRP145455
## SRR7236457 PASS SRX4142762 SRS3356559 SRP149366
## SRR7276093 PASS SRX4179700 SRS3391261 SRP149970
## SRR7293774 PASS SRX4196436 SRS3407070 SRP150311
## SRR7347194 PASS SRX4220595 SRS3421532 SRP150612
## SRR7478781 PASS SRX4348230 SRS3508075 SRP103099
## SRR7588317 PASS SRX4453577 SRS3592074 SRP155027
## SRR7889388 PASS SRX4726992 SRS3810537 SRP162329
## SRR7904770 PASS SRX4741212 SRS3822539 SRP162654
## SRR7908192 PASS SRX4744318 SRS3855914 SRP162735
## SRR7948181 PASS SRX4782130 SRS3862314 SRP163098
## SRR801695 PASS SRX258174 SRS406305 SRP020470
## SRR8528508 PASS SRX5331885 SRS4326230 SRP183532
## SRR8544036 PASS SRX5346149 SRS4337880 SRP184472
## SRR901189 PASS SRX306106 SRS445162 SRP026042
## SRR949076 PASS SRX332625 SRS468063 SRP028594
## SRR9652334 PASS SRX6413763 SRS5070852 SRP213631
## SRR9841092 PASS SRX6595812 SRS5161134 SRP216436
## SRR9874381 PASS SRX6627067 SRS5186602 SRP216966
## SRR9939088 PASS SRX6687653 SRS5245314 SRP217937
## Sample_name
## DRR017573 SAMD00009140
## DRR108715 SAMD00090951
## DRR109691 SAMD00092127
## DRR109692 SAMD00092128
## ERR1518673 SAMEA4065718
## ERR1594743 SAMEA3847037
## ERR1691932 SAMEA4514671
## ERR188129 SAMEA1573367
## ERR188184 SAMEA1573418
## ERR1910862 SAMEA103956351
## ERR1991839 SAMEA103885266
## ERR204924 SAMEA1573125
## ERR2059979 SAMEA104188614
## ERR2208954 SAMEA104411136
## ERR2303756 SAMEA104590897
## ERR2445954 SAMEA104718324
## ERR2619180 SAMEA4717818
## ERR2675483 SAMEA4766554
## ERR2700003 SAMEA4791453
## ERR3129937 SAMEA5280338
## ERR315411 SAMEA2147975
## ERR315466 SAMEA2151405
## ERR3299306 SAMEA5583174
## ERR3357674 SAMEA5693022
## ERR3490878 SAMEA5883846
## ERR576280 SAMEA2682058
## ERR752766 SAMEA3232299
## ERR752810 SAMEA3232313
## ERR866160 SAMEA3171879
## ERR973735 SAMEA3494652
## SRR10009502 GSM4041205
## SRR10068994 GSM4060364
## SRR10118992 GSM4079288
## SRR10143223 GSM4085033
## SRR10181297 GSM4095230
## SRR10259233 GSM4115622
## SRR10272816 GSM4119787
## SRR10353659 GSM4141729
## SRR10368246 GSM4144748
## SRR10446446 GSM4160405
## SRR10486655 GSM4174598
## SRR10505583 Z8
## SRR10581909 GSM4201703
## SRR10582374 GSM4202179
## SRR10604806 Exp6_HS746T_10nM
## SRR10620267 GSM4212789
## SRR10721014 GSM4222661
## SRR10741154 GSM4225682
## SRR10858280 GSM4257640
## SRR10858283 GSM4257643
## SRR11058878 GSM4305576
## SRR11058925 GSM4305640
## SRR11247856 GSM4386985
## SRR11247857 GSM4386985
## SRR11252261 GSM4392020
## SRR11290620 GSM4407382
## SRR11307901 HEK239T_RNA-seq_ABE8.17m-V106W_1
## SRR1146231 GSM1315768
## SRR11469900 NC_1_3h
## SRR11470749 GSM4451302
## SRR11542124 GSM4475898
## SRR11547440 1N
## SRR11548469 GSM4476834
## SRR11586961 GSM4490324
## SRR11615379 GSM4501055
## SRR11652607 GSM4506387
## SRR11780588 GSM4550436
## SRR11869905 RESCUE-S_rep2
## SRR1205933 mRNA-73
## SRR1272187 GSM1380719
## SRR1296129 GSM1396732
## SRR1448791 GSM1418974
## SRR1554437 GSM1482164
## SRR1576497 GSM1505847
## SRR1644195 GSM1540656
## SRR1702804 benchmark_Jurkat
## SRR1747214 GSM1580955
## SRR1777877 SCCOHT2
## SRR1947537 GSM1647005
## SRR2063343 GSM1712024
## SRR2099867 GSM1821002
## SRR2156107 HPGL0401
## SRR2313080 GSM1872068
## SRR2422379 GSM1885295
## SRR2481165 GSM1890714
## SRR2506915 Control 7
## SRR2761447 siMPLZ3_2
## SRR2970383 GSM1960716
## SRR3070185 GSM2024996
## SRR3192422 ENCODE biosample ENCBS088RNA
## SRR3213396 GSM2084200
## SRR3234008 GSM2092575
## SRR3362723 GSM2114350
## SRR3408051 GSM2130395
## SRR3471776 GSM2141391
## SRR3471926 GSM2141541
## SRR3503567 GSM2152538
## SRR3538912 GSM2157100
## SRR3644744 GSM2192672
## SRR3714679 GSM2212668
## SRR3885719 GSM2232085
## SRR3930018 GSM2241556
## SRR3932740 GSM2243023
## SRR3944326 GSM2248133
## SRR3954218 GSM2252997
## SRR3987797 GSM2256130
## SRR4007767 DMD1_Mt12
## SRR4113665 GSM2300451
## SRR4175280 NMC_cell_line_TY82
## SRR4240867 GSM2309640
## SRR4241352 GSM2309846
## SRR4255751 GSM2321864
## SRR4421980 ENCODE biosample ENCBS202CLF
## SRR4428773 GSM2350354
## SRR5032377 GSM2395561
## SRR5104192 GSM2427910
## SRR5118039 Hu8080
## SRR5124441 GSM2436466
## SRR5163544 GSM2451371
## SRR5185077 GSM2462065
## SRR5225467 GSM2475470
## SRR5225669 GSM2475672
## SRR5225767 GSM2475291
## SRR5236578 degraded.SEQC-A.5ng.rep2
## SRR5279123 GSM2500311
## SRR5305397 GSM2516926
## SRR5352626 GSM2539696
## SRR5352799 GSM2539869
## SRR542392 BR18
## SRR5444892 GSM2575400
## SRR5445642 GSM2576759
## SRR5488704 GSM2593195
## SRR5495045 GSM2596481
## SRR5528039 GSM2612489
## SRR5553974 GSM2627118
## SRR5559252 45Q-1-ESC
## SRR5676576 GSM2665632
## SRR5676577 GSM2665632
## SRR5750779 GSM2682879
## SRR5800692 GSM2692594
## SRR5802878 GSM2693234
## SRR5838317 GSM2706533
## SRR5862115 GSM2715792
## SRR5882130 C_80_RNA
## SRR5901932 GSM2733115
## SRR5902186 GSM2733369
## SRR5934783 GSM2742674
## SRR5981038 GSM2755110
## SRR5999449 GSM2770204
## SRR6000438 GSM2770728
## SRR6036044 GSM2784369
## SRR6050275 GSM2787456
## SRR6066217 GSM2791384
## SRR6149831 GSM2806812
## SRR6217804 GSM2830931
## SRR6217826 GSM2830955
## SRR6233791 P493-6, sCD40L (20ng/ml), a-IgM F(ab)2 fragments (26ng/ml), rhIGF-1 (100ng/ml), IL10 (5ng/ml)
## SRR6302566 GSM2860199
## SRR6337805 GSM2871851
## SRR6355995 GSM2392730
## SRR6369983 GSM2886127
## SRR6371359 GSM2886800
## SRR6464796 GSM2931827
## SRR6464797 GSM2931827
## SRR6464798 GSM2931827
## SRR6467601 GSM2932860
## SRR6467717 GSM2932976
## SRR6496863 GSM2942438
## SRR6503280 GSM2940525
## SRR6883165 GSM3061540
## SRR6926574 GSM3073430
## SRR6973585 GSM3090434
## SRR6978432 GSM3091270
## SRR7010505 GSM3099827
## SRR7011833 GSM3100368
## SRR7123448 GSM3131929
## SRR7130991 GSM3136673
## SRR7142047 GSM3138705
## SRR7236457 GSM3165463
## SRR7276093 GSM3178302
## SRR7293774 GSM3186685
## SRR7347194 PN-3
## SRR7478781 DFAB-92612-V0
## SRR7588317 GSM3305118
## SRR7889388 GSM3397819
## SRR7904770 GSM3402055
## SRR7908192 GSM3403196
## SRR7948181 Gene expression profiling in AuNP-treated MCF-7 cells
## SRR801695 GSM1111651
## SRR8528508 GSM3591007
## SRR8544036 GSM3593640
## SRR901189 GSM1163022
## SRR949076 GSM1203305
## SRR9652334 GSM3930435
## SRR9841092 GSM3978704
## SRR9874381 GSM3993271
## SRR9939088 GSM4024080
## GEO_series Library_name
## DRR017573 malaria8#12
## DRR108715 CRESTid1346
## DRR109691 CRESTid2426
## DRR109692 CRESTid2427
## ERR1518673 unspecified
## ERR1594743 16207243
## ERR1691932 b5_p
## ERR188129 NA19197.3.M_120202_2 extract
## ERR188184 NA19147.2.M_120131_2 extract
## ERR1910862 10380FJ0003L01
## ERR1991839 DN418836K:C3
## ERR204924 NA12045.1.M_120209_3 extract
## ERR2059979 unspecified
## ERR2208954 unspecified
## ERR2303756 Human-A017-patient-w13-2_p
## ERR2445954 Sample 6_s
## ERR2619180 HEPG2_3D_BR1_RNA_p
## ERR2675483 S8_normal_p
## ERR2700003 HGII_16293_1_p
## ERR3129937 TruSeq RNA Access
## ERR315411 V184
## ERR315466 V229
## ERR3299306 PR181_S21_p
## ERR3357674 TEC 5_s
## ERR3490878 Sample 305_p
## ERR576280 unspecified
## ERR752766 20PD01198
## ERR752810 20RD01346
## ERR866160 12655131
## ERR973735 MCF-7 untreated replicate 2
## SRR10009502 GSE136105
## SRR10068994 GSE136884
## SRR10118992 GSE137430
## SRR10143223 GSE137691
## SRR10181297 GSE137967
## SRR10259233 GSE138659
## SRR10272816 GSE138806
## SRR10353659 GSE139441
## SRR10368246 GSE139617
## SRR10446446 GSE140385
## SRR10486655 GSE138646
## SRR10505583 Z8
## SRR10581909 GSE141352
## SRR10582374 GSE141387
## SRR10604806 Exp6_HS746T_10nM
## SRR10620267 GSE141756
## SRR10721014 GSE142206
## SRR10741154 GSE142340
## SRR10858280 GSE143365
## SRR10858283 GSE143365
## SRR11058878 GSE145062
## SRR11058925 GSE145064
## SRR11247856 GSE146482
## SRR11247857 GSE146482
## SRR11252261 GSE146546
## SRR11290620 GSE146806
## SRR11307901 HEK239T_RNA-seq_ABE8.17m-V106W_1_L2
## SRR1146231
## SRR11469900 NC_1_3h
## SRR11470749 GSE147980
## SRR11542124 GSE148632
## SRR11547440 1
## SRR11548469 GSE148701
## SRR11586961 GSE149084
## SRR11615379 GSE149428
## SRR11652607 GSE149638
## SRR11780588 GSE150429
## SRR11869905 8
## SRR1205933 73-PE-IL7-1
## SRR1272187
## SRR1296129 GSE57896
## SRR1448791 GSE58740
## SRR1554437 GSE60548
## SRR1576497 GSE61476
## SRR1644195 GSE63086
## SRR1702804 hsa_rna_seq_rep_2_TRANSCRIPTOMIC
## SRR1747214 GSE64813
## SRR1777877
## SRR1947537 GSE67427
## SRR2063343 GSE69889
## SRR2099867 GSE70874
## SRR2156107 HPGL0401
## SRR2313080 GSE72790
## SRR2422379 GSE73092
## SRR2481165 GSE73318
## SRR2506915
## SRR2761447
## SRR2970383 GSE75627
## SRR3070185 GSE71812
## SRR3192422
## SRR3213396 GSE79029
## SRR3234008 GSE79338
## SRR3362723 GSE80183
## SRR3408051 GSE80537
## SRR3471776 GSE81046
## SRR3471926 GSE81046
## SRR3503567 GSE81439
## SRR3538912 GSE81550
## SRR3644744 GSE83083
## SRR3714679 GSE83687
## SRR3885719 GSE84337
## SRR3930018 GSE79843
## SRR3932740 GSE84620
## SRR3944326 GSE84712
## SRR3954218 GSE84877
## SRR3987797 GSE85011
## SRR4007767 DMD1_Mt12
## SRR4113665 GSE86337
## SRR4175280 TY_82_C5GJLACXX_TGACCA
## SRR4240867 GSE86356
## SRR4241352 GSE86884
## SRR4255751 GSE87080
## SRR4421980
## SRR4428773 GSE88858
## SRR5032377 GSE90014
## SRR5104192 GSE92346
## SRR5118039
## SRR5124441 GSE92723
## SRR5163544 GSE93326
## SRR5185077 GSE93783
## SRR5225467 GSE94438
## SRR5225669 GSE94438
## SRR5225767 GSE94437
## SRR5236578 LIB2
## SRR5279123 GSE95227
## SRR5305397 GSE95588
## SRR5352626 GSE96760
## SRR5352799 GSE96760
## SRR542392
## SRR5444892 GSE97681
## SRR5445642 GSE97744
## SRR5488704 GSE98386
## SRR5495045 GSE98454
## SRR5528039 GSE98812
## SRR5553974 GSE98894
## SRR5559252 45Q-1-ESC_fastq
## SRR5676576 GSE99944
## SRR5676577 GSE99944
## SRR5750779 GSE100427
## SRR5800692 GSE74180
## SRR5802878 GSE100785
## SRR5838317 GSE101595
## SRR5862115 GSE101794
## SRR5882130 LUSCLib_C-80_RNA
## SRR5901932 GSE102288
## SRR5902186 GSE102288
## SRR5934783 GSE102670
## SRR5981038 GSE103147
## SRR5999449 GSE103401
## SRR6000438 GSE103409
## SRR6036044 GSE103844
## SRR6050275 GSE103990
## SRR6066217 GSE104176
## SRR6149831 GSE104730
## SRR6217804 GSE106166
## SRR6217826 GSE106169
## SRR6233791 P493-6 combination 26
## SRR6302566 GSE107047
## SRR6337805 GSE107593
## SRR6355995 GSE89895
## SRR6369983 GSE107992
## SRR6371359 GSE108012
## SRR6464796 GSE109108
## SRR6464797 GSE109108
## SRR6464798 GSE109108
## SRR6467601 GSE109142
## SRR6467717 GSE109142
## SRR6496863 GSE109409
## SRR6503280 GSE109367
## SRR6883165 GSE112243
## SRR6926574 GSE112594
## SRR6973585 GSE112883
## SRR6978432 GSE112927
## SRR7010505 GSE113194
## SRR7011833 GSE113210
## SRR7123448 GSE114065
## SRR7130991 GSE114159
## SRR7142047 GSE114273
## SRR7236457 GSE115112
## SRR7276093 GSE115442
## SRR7293774 GSE115650
## SRR7347194 PN-3
## SRR7478781 DFAB-92612-V0
## SRR7588317 GSE117610
## SRR7889388 GSE120297
## SRR7904770 GSE120502
## SRR7908192 GSE120562
## SRR7948181 SAMN09976708
## SRR801695 GSE45669
## SRR8528508 GSE126078
## SRR8544036 GSE126207
## SRR901189 GSE47944
## SRR949076 GSE48173
## SRR9652334 GSE133942
## SRR9841092 GSE134908
## SRR9874381 GSE135192
## SRR9939088 GSE135635saveRDS(orgMetadataPass, "orgMetadataPass.rds")
# Put the filtered org GeneCount data and the filtered metadata dataframes into a list
orgCountMetadata <- list(GeneCounts = orgPassWide, MetadataSummary = orgMetadataPass)
# Apply both dataframes to the function
head(orgCountMetadata)## $GeneCounts
## DRR017573 DRR108715 DRR109691 DRR109692 ERR1518673 ERR1594743
## ENSG00000223972 1 0 0 0 0 0
## ENSG00000227232 0 0 0 0 12 20
## ENSG00000278267 0 0 0 0 2 1
## ENSG00000243485 0 0 0 0 1 0
## ENSG00000284332 0 0 0 0 0 0
## ENSG00000237613 0 0 0 0 0 0
## ENSG00000268020 0 0 0 0 0 0
## ENSG00000240361 0 0 0 0 0 1
## ENSG00000186092 0 0 0 0 0 0
## ENSG00000238009 6 0 0 0 0 1
## ENSG00000239945 0 0 0 0 0 0
## ENSG00000233750 0 0 0 0 0 0
## ENSG00000268903 387 14 98 92 2 37
## ENSG00000269981 174 6 21 20 2 28
## ENSG00000239906 0 0 0 0 0 0
## ENSG00000241860 11 0 2 3 1 6
## ENSG00000222623 0 0 0 0 0 0
## ENSG00000241599 0 0 0 0 0 0
## ENSG00000279928 0 0 0 0 0 0
## ENSG00000279457 32 16 8 12 30 40
## ENSG00000273874 0 0 0 0 0 0
## ENSG00000228463 2 1 0 0 3 6
## ENSG00000236679 0 0 0 0 0 0
## ENSG00000236601 0 0 0 0 0 0
## ENSG00000237094 68 13 29 34 3 31
## ENSG00000269732 0 0 0 0 0 0
## ENSG00000284733 0 0 0 0 0 0
## ENSG00000233653 0 0 0 0 0 0
## ENSG00000250575 0 0 0 0 0 0
## ENSG00000278757 0 1 0 0 0 0
## ENSG00000230021 2 0 0 0 1 1
## ENSG00000235146 0 0 0 0 0 0
## ENSG00000225972 2 7 19 21 6 0
## ENSG00000225630 1182 595 675 869 2448 953
## ENSG00000237973 86 262 157 196 4121 378
## ENSG00000278791 0 0 0 0 0 0
## ENSG00000229344 8 51 76 112 15 10
## ENSG00000240409 2 2 7 5 4 0
## ENSG00000248527 1937 3976 8511 12888 18068 7471
## ENSG00000198744 6 30 45 61 48 3
## ENSG00000268663 0 0 0 0 0 0
## ENSG00000284662 0 0 0 0 0 0
## ENSG00000229376 1 0 0 0 0 0
## ENSG00000228327 25 10 19 17 13 52
## ENSG00000223181 0 0 0 0 0 0
## ENSG00000229905 0 0 0 0 0 0
## ENSG00000237491 6 19 12 14 9 11
## ENSG00000230092 8 1 0 0 0 3
## ENSG00000177757 3 0 0 0 4 0
## ENSG00000228794 137 199 76 112 119 154
## ENSG00000225880 7 8 15 13 9 11
## ENSG00000230368 0 0 0 0 0 0
## ENSG00000234711 0 0 0 0 0 0
## ENSG00000283040 0 0 0 0 0 0
## ENSG00000272438 0 6 2 2 0 2
## ENSG00000230699 1 30 10 28 0 9
## ENSG00000241180 0 1 0 0 0 0
## ENSG00000223764 1 25 2 13 12 2
## ENSG00000187634 2 381 15 103 22 34
## ENSG00000188976 662 2266 3267 3598 756 2980
## ENSG00000187961 163 217 162 200 37 352
## ENSG00000187583 13 9 27 58 6 10
## ENSG00000187642 10 2 0 0 2 0
## ENSG00000272512 6 134 1 6 2 11
## ENSG00000188290 88 157 8 49 74 115
## ENSG00000187608 915 126 95 154 294 202
## ENSG00000231702 0 0 0 0 0 0
## ENSG00000224969 1 1 0 0 0 0
## ENSG00000188157 216 5553 2168 2906 2375 6236
## ENSG00000242590 0 0 0 0 0 0
## ENSG00000217801 43 21 20 25 21 35
## ENSG00000273443 4 0 0 0 0 0
## ENSG00000237330 0 0 0 0 0 0
## ENSG00000131591 352 171 149 219 66 238
## ENSG00000223823 1 0 0 0 0 0
## ENSG00000207730 0 0 0 0 1 0
## ENSG00000207607 0 0 0 0 1 1
## ENSG00000198976 0 0 0 0 2 0
## ENSG00000272141 1 0 0 2 16 5
## ENSG00000205231 2 0 0 0 0 0
## ENSG00000162571 3 0 0 0 1 9
## ENSG00000186891 251 0 0 0 2 12
## ENSG00000186827 194 0 0 0 18 0
## ENSG00000078808 2111 1284 1117 1680 2553 1597
## ENSG00000176022 283 425 204 364 476 315
## ENSG00000184163 151 5 8 12 2 55
## ENSG00000260179 26 1 2 1 0 4
## ENSG00000160087 1252 1418 845 905 599 926
## ENSG00000230415 9 7 4 6 0 3
## ENSG00000162572 119 60 9 26 8 39
## ENSG00000131584 930 1320 226 284 187 465
## ENSG00000278073 0 0 0 0 0 0
## ENSG00000169972 99 374 282 336 38 463
## ENSG00000127054 1496 1062 1251 1841 881 1645
## ENSG00000283712 0 0 0 0 0 0
## ENSG00000240731 19 7 11 9 11 24
## ENSG00000224051 651 227 150 220 323 214
## ENSG00000169962 61 2 0 1 6 0
## ENSG00000107404 578 633 658 830 696 1307
## ENSG00000284372 0 0 0 0 0 0
## ENSG00000162576 75 519 86 86 1395 262
## ENSG00000175756 1270 940 1139 1375 1544 1479
## ENSG00000223663 0 0 0 0 0 0
## ENSG00000221978 3155 1991 1064 1285 834 1653
## ENSG00000224870 269 316 264 339 367 297
## ENSG00000242485 763 1009 1287 1373 1822 979
## ENSG00000264293 0 0 0 0 0 0
## ENSG00000272455 22 46 61 87 25 97
## ENSG00000235098 1 66 4 25 71 60
## ENSG00000225905 0 0 0 1 2 5
## ENSG00000205116 1 0 7 8 0 21
## ENSG00000225285 0 1 2 6 2 26
## ENSG00000179403 1 491 361 417 862 1295
## ENSG00000215915 4 12 0 4 463 44
## ENSG00000160072 384 214 553 367 116 414
## ENSG00000284740 2 0 1 1 12 11
## ENSG00000197785 71 327 772 831 250 802
## ENSG00000205090 3 50 17 26 37 71
## ENSG00000160075 2573 1901 2475 2988 2932 2593
## ENSG00000215014 14 4 10 16 33 6
## ENSG00000274481 0 0 0 0 0 0
## ENSG00000228594 32 51 515 738 242 288
## ENSG00000272106 155 84 37 104 524 95
## ENSG00000197530 742 385 173 350 639 519
## ENSG00000189409 1 12 4 8 6 28
## ENSG00000248333 829 432 466 702 394 876
## ENSG00000272004 0 3 2 0 0 1
## ENSG00000189339 1007 1443 616 892 821 628
## ENSG00000269737 102 0 1 4 21 0
## ENSG00000215914 0 0 0 0 0 4
## ENSG00000008128 151 6 8 17 11 11
## ENSG00000268575 24 42 23 61 7 44
## ENSG00000227775 43 0 0 1 67 0
## ENSG00000215790 21 53 21 53 24 58
## ENSG00000008130 4398 657 718 1276 648 1548
## ENSG00000078369 10995 1779 6570 10122 4811 10538
## ENSG00000231050 4 2 3 3 12 2
## ENSG00000169885 6 4 2 6 4 2
## ENSG00000178821 0 27 94 113 13 142
## ENSG00000142609 0 2 1 4 1 4
## ENSG00000233542 0 0 0 4 0 13
## ENSG00000187730 0 10 14 15 9 30
## ENSG00000226969 0 0 0 0 0 0
## ENSG00000067606 124 648 549 891 318 1084
## ENSG00000271806 5 0 2 0 0 0
## ENSG00000182873 60 48 9 16 15 28
## ENSG00000162585 783 633 410 684 637 778
## ENSG00000234396 0 0 0 0 0 0
## ENSG00000157933 4069 2547 2450 2580 1117 3325
## ENSG00000116151 23 111 73 118 185 72
## ENSG00000272161 0 0 0 1 1 0
## ENSG00000269896 5 56 20 47 54 16
## ENSG00000272420 5 8 6 7 3 1
## ENSG00000157916 525 908 939 1151 1790 1251
## ENSG00000157911 89 197 507 693 288 447
## ENSG00000149527 177 221 4 2 35 4
## ENSG00000224387 0 0 0 0 2 0
## ENSG00000229393 2 1 0 0 0 1
## ENSG00000157881 889 298 316 590 370 644
## ENSG00000197921 1 2 2 0 1 4
## ENSG00000272449 305 2 13 14 28 17
## ENSG00000238164 94 0 0 0 9 0
## ENSG00000157873 7560 4 0 0 367 4
## ENSG00000225931 7 0 0 0 0 0
## ENSG00000228037 44 0 0 0 2 0
## ENSG00000157870 317 431 814 981 324 1013
## ENSG00000142606 10 1 0 1 19 60
## ENSG00000237058 0 0 0 0 0 10
## ENSG00000215912 51 0 0 0 39 8
## ENSG00000283259 0 0 0 0 0 0
## ENSG00000233234 0 0 0 0 0 0
## ENSG00000231630 0 0 0 0 0 0
## ENSG00000284745 0 0 0 0 0 0
## ENSG00000169717 0 0 0 0 0 2
## ENSG00000177133 1 12 0 6 218 0
## ENSG00000142611 2 1 18 68 475 54
## ENSG00000283572 0 0 0 0 0 0
## ENSG00000226286 0 0 0 0 1 0
## ENSG00000279839 0 0 0 0 1 0
## ENSG00000272235 0 0 0 0 6 0
## ENSG00000130762 3 294 468 630 298 487
## ENSG00000272088 0 11 0 2 1 2
## ENSG00000162591 575 577 129 289 211 386
## ENSG00000207776 0 0 0 0 0 0
## ENSG00000238260 7 3 1 4 2 7
## ENSG00000158109 1384 688 534 733 1697 928
## ENSG00000116213 350 493 382 625 183 514
## ENSG00000078900 5 480 45 174 8 301
## ENSG00000227589 0 0 0 0 0 0
## ENSG00000235131 0 0 0 0 0 0
## ENSG00000227372 384 793 490 911 460 915
## ENSG00000276189 0 0 0 0 0 0
## ENSG00000162592 0 0 1 3 5 6
## ENSG00000235169 59 3 4 16 124 13
## ENSG00000130764 689 1550 2206 2837 857 2474
## ENSG00000266075 2 0 0 0 0 0
## ENSG00000272153 13 3 1 1 6 1
## ENSG00000116198 208 1029 559 742 452 749
## ENSG00000169598 115 82 192 218 45 162
## ENSG00000198912 526 335 380 439 244 473
## ENSG00000236423 2 17 3 7 1 6
## ENSG00000233304 0 4 0 0 0 0
## ENSG00000226374 0 0 0 0 0 0
## ENSG00000284668 0 0 0 1 0 0
## ENSG00000284703 0 1 0 1 0 1
## ENSG00000229280 2 0 0 0 0 0
## ENSG00000235054 0 0 0 0 0 0
## ENSG00000284694 1 0 0 0 0 0
## ENSG00000227169 0 0 0 0 0 0
## ENSG00000232596 0 0 0 0 0 0
## ENSG00000196581 27 917 448 373 30 99
## ENSG00000284739 0 0 0 0 0 0
## ENSG00000284674 0 0 0 0 0 0
## ENSG00000231510 0 0 2 0 0 0
## ENSG00000284616 0 0 0 0 2 0
## ENSG00000284692 0 1 0 0 0 0
## ENSG00000284666 0 0 0 0 0 0
## ENSG00000260972 0 0 0 0 0 0
## ENSG00000283356 0 0 0 0 0 0
## ENSG00000236948 1 0 0 2 0 1
## ENSG00000264341 0 0 0 0 0 0
## ENSG00000264101 0 0 0 0 0 0
## ENSG00000131697 155 274 210 273 229 308
## ENSG00000069424 6734 154 29 179 134 347
## ENSG00000116254 4 4 81 77 3 67
## ENSG00000116251 3146 1675 1385 2050 14300 6559
## ENSG00000226944 0 0 3 3 7 1
## ENSG00000158286 24 9 26 44 70 51
## ENSG00000116237 123 2568 4002 5258 1727 4040
## ENSG00000225077 0 16 56 74 0 72
## ENSG00000173673 1 2 616 817 0 1049
## ENSG00000158292 54 20 185 537 56 395
## ENSG00000097021 88 950 1983 2654 123 2503
## ENSG00000271746 0 0 0 3 0 0
## ENSG00000069812 2 16 25 53 5 33
## ENSG00000187017 41 53 128 402 2 371
## ENSG00000265392 0 0 0 0 0 0
## ENSG00000231868 1 0 0 0 0 0
## ENSG00000215788 1773 69 72 88 16 103
## ENSG00000171680 83 614 348 665 92 667
## ENSG00000162408 1119 903 1124 1061 88 836
## ENSG00000253022 0 0 0 0 0 0
## ENSG00000229519 2 0 0 0 0 0
## ENSG00000173662 6 0 0 3 0 1
## ENSG00000204859 851 184 208 318 326 286
## ENSG00000162413 1706 544 666 468 465 561
## ENSG00000116273 545 575 779 1134 219 1567
## ENSG00000041988 297 148 103 174 375 213
## ENSG00000007923 437 1158 2708 2917 398 2024
## ENSG00000228750 0 0 0 0 4 0
## ENSG00000284744 0 0 0 0 0 0
## ENSG00000237436 2 5 4 5 16 13
## ENSG00000171735 330 643 545 1019 642 1088
## ENSG00000227950 0 0 0 0 0 0
## ENSG00000237365 0 0 0 0 0 0
## ENSG00000207056 0 0 0 0 0 0
## ENSG00000237402 0 0 1 2 0 0
## ENSG00000237728 0 0 0 0 0 0
## ENSG00000225126 0 0 0 0 0 0
## ENSG00000270171 0 6 1 14 1 1
## ENSG00000270035 0 3 0 2 0 1
## ENSG00000269978 0 11 2 7 0 3
## ENSG00000049245 946 504 589 1063 2378 1297
## ENSG00000269925 10 10 4 4 2 6
## ENSG00000049246 70 34 123 338 490 459
## ENSG00000236266 1 0 0 0 3 0
## ENSG00000049247 186 0 1 0 17 1
## ENSG00000049249 130 0 0 0 0 0
## ENSG00000270330 0 0 0 0 0 0
## ENSG00000116288 1514 1922 2342 3015 6120 3010
## ENSG00000200344 1 0 0 0 0 0
## ENSG00000284747 0 5 2 1 0 5
## ENSG00000284716 1 0 0 1 0 0
## ENSG00000116285 22 459 1337 1120 921 898
## ENSG00000238290 0 2 0 0 10 1
## ENSG00000232848 0 2 1 3 1 1
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## ENSG00000227775 1 487
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## ENSG00000078369 4363 16363
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## ENSG00000069424 6257 6721
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## ENSG00000116237 600 1641
## ENSG00000225077 1 1
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## ENSG00000097021 338 821
## ENSG00000271746 0 0
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## ENSG00000265392 0 0
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## ENSG00000215788 1307 229
## ENSG00000171680 13 22
## ENSG00000162408 333 339
## ENSG00000253022 0 0
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## ENSG00000162413 697 1389
## ENSG00000116273 268 65
## ENSG00000041988 151 242
## ENSG00000007923 666 662
## ENSG00000228750 0 0
## ENSG00000284744 0 0
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## ENSG00000171735 192 370
## ENSG00000227950 0 0
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## ENSG00000237402 0 1
## ENSG00000237728 0 0
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## ENSG00000270171 0 0
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## ENSG00000269978 0 0
## ENSG00000049245 1474 1211
## ENSG00000269925 13 11
## ENSG00000049246 854 63
## ENSG00000236266 0 1
## ENSG00000049247 4 1
## ENSG00000049249 41 3
## ENSG00000270330 0 0
## ENSG00000116288 1010 7142
## ENSG00000200344 0 3
## ENSG00000284747 12 54
## ENSG00000284716 0 0
## ENSG00000116285 42 7
## ENSG00000238290 0 0
## ENSG00000232848 0 0
## ENSG00000229305 0 0
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## ENSG00000233645 0 0
## ENSG00000251977 0 0
## ENSG00000162426 0 2
## ENSG00000252254 0 0
## ENSG00000142599 1103 5164
## ENSG00000232912 5 24
## ENSG00000221083 0 1
## ENSG00000270282 0 0
## ENSG00000234619 0 0
## ENSG00000224315 0 0
## ENSG00000222511 1 0
## ENSG00000226545 0 0
## ENSG00000228423 0 1
## ENSG00000229716 0 0
## ENSG00000074800 11392 9004
## ENSG00000274258 0 0
## ENSG00000236269 2 4
## ENSG00000230679 0 0
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## ENSG00000238249 0 0
## ENSG00000232208 4 0
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## ENSG00000265141 0 0
## ENSG00000197241 1 0
## ENSG00000142583 359 5
## ENSG00000252404 0 0
## ENSG00000180758 114 13
## ENSG00000228526 280 1
## ENSG00000284357 0 0
## ENSG00000234546 4 0
## ENSG00000281937 0 0
## ENSG00000049239 1141 1120
## ENSG00000171621 796 5
## ENSG00000284652 0 0
## ENSG00000284693 3 0
## ENSG00000252956 0 0
## ENSG00000235263 0 0
## ENSG00000171612 80 255
## ENSG00000231181 5 2
## ENSG00000188807 112 766
## ENSG00000171608 3134 11765
## ENSG00000179840 6 195
## ENSG00000233268 0 1
## ENSG00000231789 2 1
## ENSG00000171603 1040 3895
## ENSG00000271264 0 0
## ENSG00000280113 0 0
## ENSG00000178585 240 357
## ENSG00000223989 0 0
## ENSG00000162441 453 604
## ENSG00000228150 2 2
## ENSG00000173614 243 166
## ENSG00000202415 2 5
## ENSG00000283611 0 0
## ENSG00000265521 0 0
## ENSG00000241326 0 0
## ENSG00000162444 176 18
## ENSG00000130939 934 1123
## ENSG00000224340 0 0
## ENSG00000233623 2 6
## ENSG00000201746 0 0
## ENSG00000054523 1313 1076
## ENSG00000264881 0 0
## ENSG00000199562 0 0
## ENSG00000264501 0 0
## ENSG00000284735 0 7
## ENSG00000284642 5 13
## ENSG00000142657 8530 6094
## ENSG00000271989 0 0
## ENSG00000251503 0 2
## ENSG00000175279 5 2
## ENSG00000241563 0 9
## ENSG00000160049 590 912
## ENSG00000203469 1 0
## ENSG00000142655 446 323
## ENSG00000243267 0 0
## ENSG00000130940 48 420
## ENSG00000272078 0 35
## ENSG00000225158 0 0
## ENSG00000175262 44 37
## ENSG00000215785 0 0
## ENSG00000120948 1022 1639
## ENSG00000277726 0 0
## ENSG00000009724 1 250
## ENSG00000271895 36 44
## ENSG00000116649 416 1064
## ENSG00000171824 1158 1179
## ENSG00000226849 14 5
## ENSG00000230337 3 0
## ENSG00000198793 1188 2156
## ENSG00000225602 0 1
## ENSG00000253086 0 0
## ENSG00000171819 0 0
## ENSG00000207451 0 0
## ENSG00000238173 0 0
## ENSG00000120942 394 773
## ENSG00000238199 0 6
## ENSG00000284646 0 0
## ENSG00000224338 0 0
## ENSG00000204624 0 0
## ENSG00000235643 0 0
## ENSG00000284708 0 0
## ENSG00000116661 13 5
## ENSG00000132879 352 500
## ENSG00000116663 207 483
## ENSG00000116670 245 1151
## ENSG00000162490 23 7
## ENSG00000177674 531 271
## ENSG00000215910 0 0
## ENSG00000177553 0 0
## ENSG00000177000 1236 763
## ENSG00000011021 585 500
## ENSG00000242349 13 8
## ENSG00000276470 0 0
## ENSG00000278852 0 0
## ENSG00000175206 0 3
## ENSG00000275915 0 0
## ENSG00000120937 0 0
## ENSG00000224904 0 0
## ENSG00000199347 1 0
## ENSG00000201801 0 5
## ENSG00000116685 518 3196
## ENSG00000083444 1127 547
## ENSG00000116688 1339 1591
## ENSG00000270914 0 0
## ENSG00000116691 322 3469
## ENSG00000202461 0 9
## ENSG00000276869 0 0
## ENSG00000243539 0 0
## ENSG00000120949 18 77
## ENSG00000201135 0 0
## ENSG00000227875 0 0
## ENSG00000283789 0 0
## ENSG00000028137 1803 4545
## ENSG00000263676 0 0
## ENSG00000225196 0 0
## ENSG00000252969 0 0
## ENSG00000048707 1693 3533
## ENSG00000239149 0 7
## ENSG00000229484 4 1
## ENSG00000162496 154 30
## ENSG00000221340 0 1
## ENSG00000276830 1 0
## ENSG00000272482 0 0
## ENSG00000204518 0 0
## ENSG00000226166 0 0
## ENSG00000188984 0 0
## ENSG00000157330 0 0
## ENSG00000116726 0 0
## ENSG00000116721 0 0
## ENSG00000228338 0 0
## ENSG00000239810 0 0
## ENSG00000231103 0 0
## ENSG00000179172 0 0
## ENSG00000120952 0 0
## ENSG00000243073 0 0
## ENSG00000187545 0 0
## ENSG00000204510 0 0
## ENSG00000207434 0 0
## ENSG00000234064 0 0
## ENSG00000232423 0 0
## ENSG00000274178 0 0
## ENSG00000274764 0 0
## ENSG00000277058 0 0
## ENSG00000229571 0 0
## ENSG00000277862 0 0
## ENSG00000236179 0 0
## ENSG00000275774 0 0
## ENSG00000229978 0 0
## ENSG00000233336 0 0
## ENSG00000280267 0 0
## ENSG00000179412 0 0
## ENSG00000204505 0 0
## ENSG00000279169 0 0
## ENSG00000279804 0 0
## ENSG00000250894 0 0
## ENSG00000270601 0 0
## ENSG00000231219 0 0
## ENSG00000207511 0 0
## ENSG00000182330 0 0
## ENSG00000237700 0 0
## ENSG00000204501 0 0
## ENSG00000228229 0 0
## ENSG00000204481 0 0
## ENSG00000204480 0 0
## ENSG00000204479 0 0
## ENSG00000204478 0 0
## ENSG00000162494 0 19
## ENSG00000259961 0 0
## ENSG00000215909 0 0
## ENSG00000162493 2 0
## ENSG00000222952 0 2
## ENSG00000237445 0 0
## ENSG00000253085 0 0
## ENSG00000116731 892 2022
## ENSG00000189337 11 1
## ENSG00000252151 0 0
## ENSG00000231606 0 0
## ENSG00000234593 0 0
## ENSG00000235829 0 0
## ENSG00000175147 3 0
## ENSG00000171729 139 15
## ENSG00000204464 0 0
## ENSG00000215720 0 0
## ENSG00000278480 3 0
## ENSG00000142621 3 0
## ENSG00000233485 0 0
## ENSG00000236045 0 0
## ENSG00000228140 3 2
## ENSG00000142634 1652 3914
## ENSG00000162438 1 7
## ENSG00000142615 0 0
## ENSG00000215704 0 0
## ENSG00000132906 164 588
## ENSG00000116138 378 266
## ENSG00000251866 0 0
## ENSG00000272510 0 0
## ENSG00000116771 77 8
## ENSG00000237301 1 0
## ENSG00000235084 0 4
## ENSG00000252417 0 0
## ENSG00000236500 0 0
## ENSG00000197312 1650 1870
## ENSG00000215695 0 0
## ENSG00000271742 0 1
## ENSG00000116786 3015 2279
## ENSG00000237938 0 19
## [ reached 'max' / getOption("max.print") -- omitted 57795 rows ]
##
## $MetadataSummary
## QC_summary SRX_accession SRS_accession SRP_accession
## DRR017573 PASS DRX015849 DRS015339 DRP001953
## DRR108715 PASS DRX101804 DRS110100 DRP005525
## DRR109691 PASS DRX102780 DRS111076 DRP005525
## DRR109692 PASS DRX102781 DRS111077 DRP005525
## ERR1518673 PASS ERX1589652 ERS1236828 ERP012979
## ERR1594743 PASS ERX1665329 ERS1461229 ERP007111
## ERR1691932 PASS ERX1761560 ERS1413850 ERP017989
## ERR188129 PASS ERX163089 ERS185054 ERP001942
## ERR188184 PASS ERX162902 ERS185087 ERP001942
## ERR1910862 PASS ERX1971342 ERS1645519 ERP022368
## ERR1991839 PASS ERX2051727 ERS2004882 ERP022909
## ERR204924 PASS ERX179574 ERS185387 ERP001942
## ERR2059979 PASS ERX2119036 ERS1847632 ERP024173
## ERR2208954 PASS ERX2263312 ERS2029078 ERP105482
## ERR2303756 PASS ERX2355092 ERS2202179 ERP106849
## ERR2445954 PASS ERX2465055 ERS2319707 ERP107676
## ERR2619180 PASS ERX2636877 ERS2537965 ERP109267
## ERR2675483 PASS ERX2690581 ERS2586517 ERP109626
## ERR2700003 PASS ERX2714390 ERS2611382 ERP109918
## ERR3129937 PASS ERX3159179 ERS3087609 ERP110841
## ERR315411 PASS ERX288566 ERS326969 ERP003613
## ERR315466 PASS ERX288542 ERS326982 ERP003613
## ERR3299306 PASS ERX3325584 ERS3387401 ERP115010
## ERR3357674 PASS ERX3382181 ERS3496984 ERP115637
## ERR3490878 PASS ERX3512278 ERS3672302 ERP115010
## ERR576280 PASS ERX534692 ERS518723 ERP006577
## ERR752766 PASS ERX696448 ERS653509 ERP009437
## ERR752810 PASS ERX696492 ERS653523 ERP009437
## ERR866160 PASS ERX945788 ERS626270 ERP008967
## ERR973735 PASS ERX1050718 ERS801801 ERP011233
## SRR10009502 PASS SRX6747727 SRS5297959 SRP218977
## SRR10068994 PASS SRX6802628 SRS5347217 SRP220372
## SRR10118992 PASS SRX6848484 SRS5387029 SRP221604
## SRR10143223 PASS SRX6871148 SRS5407179 SRP222478
## SRR10181297 PASS SRX6902647 SRS5434544 SRP223239
## SRR10259233 PASS SRX6977105 SRS5496382 SRP225086
## SRR10272816 PASS SRX6986027 SRS5509216 SRP225441
## SRR10353659 PASS SRX7063371 SRS5580115 SRP227161
## SRR10368246 PASS SRX7076240 SRS5592125 SRP227534
## SRR10446446 PASS SRX7141157 SRS5649298 SRP229963
## SRR10486655 PASS SRX7175968 SRS5682849 SRP230422
## SRR10505583 PASS SRX7194439 SRS5700376 SRP230868
## SRR10581909 PASS SRX7262339 SRS5757898 SRP234536
## SRR10582374 PASS SRX7262734 SRS5758291 SRP234568
## SRR10604806 PASS SRX7284285 SRS5777960 SRP235049
## SRR10620267 PASS SRX7299361 SRS5792599 SRP235561
## SRR10721014 PASS SRX7397669 SRS5845447 SRP237940
## SRR10741154 PASS SRX7416696 SRS5863503 SRP238240
## SRR10858280 PASS SRX7528404 SRS5967752 SRP240916
## SRR10858283 PASS SRX7528407 SRS5967755 SRP240916
## SRR11058878 PASS SRX7704819 SRS6128723 SRP248023
## SRR11058925 PASS SRX7704863 SRS6128767 SRP248025
## SRR11247856 PASS SRX7858323 SRS6267402 SRP251766
## SRR11247857 PASS SRX7858323 SRS6267402 SRP251766
## SRR11252261 PASS SRX7862381 SRS6271227 SRP251874
## SRR11290620 PASS SRX7896200 SRS6304765 SRP252428
## SRR11307901 PASS SRX7912999 SRS6319939 SRP223274
## SRR1146231 PASS SRX451455 SRS544667 SRP035988
## SRR11469900 PASS SRX8046405 SRS6417876 SRP254985
## SRR11470749 PASS SRX8047188 SRS6418628 SRP255013
## SRR11542124 PASS SRX8112222 SRS6477308 SRP256329
## SRR11547440 PASS SRX8117425 SRS6482351 SRP256409
## SRR11548469 PASS SRX8118494 SRS6483205 SRP256445
## SRR11586961 PASS SRX8154512 SRS6516808 SRP257863
## SRR11615379 PASS SRX8181746 SRS6540815 SRP258718
## SRR11652607 PASS SRX8213646 SRS6572874 SRP259314
## SRR11780588 PASS SRX8333139 SRS6652542 SRP261333
## SRR11869905 PASS SRX8419901 SRS6731427 SRP265176
## SRR1205933 PASS SRX501751 SRS582803 SRP040547
## SRR1272187 PASS SRX533781 SRS602509 SRP041706
## SRR1296129 PASS SRX550560 SRS618302 SRP042186
## SRR1448791 PASS SRX620751 SRS645155 SRP043510
## SRR1554437 PASS SRX683722 SRS686890 SRP045632
## SRR1576497 PASS SRX702197 SRS702061 SRP047194
## SRR1644195 PASS SRX753525 SRS738884 SRP049607
## SRR1702804 PASS SRX803956 SRS785863 SRP051039
## SRR1747214 PASS SRX834804 SRS812794 SRP051848
## SRR1777877 PASS SRX857514 SRS829464 SRP052896
## SRR1947537 PASS SRX974107 SRS889297 SRP056733
## SRR2063343 PASS SRX1059116 SRS961371 SRP059509
## SRR2099867 PASS SRX1094558 SRS989980 SRP061037
## SRR2156107 PASS SRX1143101 SRS1029380 SRP062278
## SRR2313080 PASS SRX1210926 SRS1060813 SRP063493
## SRR2422379 PASS SRX1250328 SRS1071360 SRP063851
## SRR2481165 PASS SRX1272402 SRS1079518 SRP063980
## SRR2506915 PASS SRX1282716 SRS1089571 SRP064138
## SRR2761447 PASS SRX1366803 SRS1128611 SRP065120
## SRR2970383 PASS SRX1459612 SRS1187057 SRP066917
## SRR3070185 PASS SRX1510918 SRS1230774 SRP062130
## SRR3192422 PASS SRX1603406 SRS1312897 SRP013565
## SRR3213396 PASS SRX1620842 SRS1329623 SRP071331
## SRR3234008 PASS SRX1639653 SRS1346263 SRP071932
## SRR3362723 PASS SRX1693989 SRS1395130 SRP073191
## SRR3408051 PASS SRX1717157 SRS1405935 SRP073667
## SRR3471776 PASS SRX1739134 SRS1419340 SRP074274
## SRR3471926 PASS SRX1739284 SRS1419490 SRP074274
## SRR3503567 PASS SRX1761117 SRS1436886 SRP075117
## SRR3538912 PASS SRX1770950 SRS1443235 SRP075319
## SRR3644744 PASS SRX1828952 SRS1490523 SRP076235
## SRR3714679 PASS SRX1874075 SRS1523921 SRP077046
## SRR3885719 PASS SRX1940990 SRS1559775 SRP078417
## SRR3930018 PASS SRX1959652 SRS1569757 SRP078912
## SRR3932740 PASS SRX1962063 SRS1571967 SRP078990
## SRR3944326 PASS SRX1970316 SRS1579373 SRP079342
## SRR3954218 PASS SRX1978468 SRS1586017 SRP079926
## SRR3987797 PASS SRX1989824 SRS1593654 SRP080367
## SRR4007767 PASS SRX2006122 SRS1605070 SRP078945
## SRR4113665 PASS SRX2086813 SRS1663028 SRP083954
## SRR4175280 PASS SRX2140530 SRS1661888 SRP083924
## SRR4240867 PASS SRX2161836 SRS1689988 SRP089788
## SRR4241352 PASS SRX2162324 SRS1690381 SRP089814
## SRR4255751 PASS SRX2175516 SRS1702804 SRP090124
## SRR4421980 PASS SRX2244269 SRS1745028 SRP013565
## SRR4428773 PASS SRX2250297 SRS1750267 SRP091695
## SRR5032377 PASS SRX2357303 SRS1806120 SRP093793
## SRR5104192 PASS SRX2420094 SRS1857412 SRP095037
## SRR5118039 PASS SRX2270678 SRS1761491 SRP092132
## SRR5124441 PASS SRX2439426 SRS1874042 SRP095491
## SRR5163544 PASS SRX2480703 SRS1912325 SRP096338
## SRR5185077 PASS SRX2501099 SRS1927481 SRP096982
## SRR5225467 PASS SRX2534583 SRS1955185 SRP098758
## SRR5225669 PASS SRX2534785 SRS1955387 SRP098758
## SRR5225767 PASS SRX2534883 SRS1955484 SRP098761
## SRR5236578 PASS SRX2543640 SRS1962707 SRP097611
## SRR5279123 PASS SRX2582949 SRS1996925 SRP100570
## SRR5305397 PASS SRX2606829 SRS2018106 SRP100947
## SRR5352626 PASS SRX2648853 SRS2054064 SRP102077
## SRR5352799 PASS SRX2649026 SRS2054236 SRP102077
## SRR542392 PASS SRX176430 SRS356035 SRP014830
## SRR5444892 PASS SRX2733947 SRS2121843 SRP103828
## SRR5445642 PASS SRX2734637 SRS2122503 SRP103864
## SRR5488704 PASS SRX2771550 SRS2154964 SRP105769
## SRR5495045 PASS SRX2776002 SRS2159290 SRP106049
## SRR5528039 PASS SRX2797234 SRS2178204 SRP106875
## SRR5553974 PASS SRX2819432 SRS2197584 SRP107025
## SRR5559252 PASS SRX2822371 SRS2199454 SRP107072
## SRR5676576 PASS SRX2912081 SRS2278368 SRP109030
## SRR5676577 PASS SRX2912081 SRS2278368 SRP109030
## SRR5750779 PASS SRX2951000 SRS2309424 SRP110289
## SRR5800692 PASS SRX2980159 SRS2333375 SRP110994
## SRR5802878 PASS SRX2982219 SRS2335278 SRP111061
## SRR5838317 PASS SRX3014615 SRS2364367 SRP112756
## SRR5862115 PASS SRX3030761 SRS2379649 SRP113470
## SRR5882130 PASS SRX3048805 SRS2395581 SRP114315
## SRR5901932 PASS SRX3063498 SRS2408888 SRP114871
## SRR5902186 PASS SRX3063752 SRS2408638 SRP114871
## SRR5934783 PASS SRX3094923 SRS2432096 SRP115470
## SRR5981038 PASS SRX3137041 SRS2469919 SRP116272
## SRR5999449 PASS SRX3154924 SRS2486760 SRP116913
## SRR6000438 PASS SRX3155896 SRS2487529 SRP116955
## SRR6036044 PASS SRX3184884 SRS2513325 SRP117629
## SRR6050275 PASS SRX3197275 SRS2524358 SRP118077
## SRR6066217 PASS SRX3209589 SRS2534582 SRP118760
## SRR6149831 PASS SRX3261849 SRS2575034 SRP119607
## SRR6217804 PASS SRX3326445 SRS2630194 SRP121472
## SRR6217826 PASS SRX3326455 SRS2630204 SRP121474
## SRR6233791 PASS SRX3342181 SRS2643587 SRP094756
## SRR6302566 PASS SRX3403476 SRS2706058 SRP125179
## SRR6337805 PASS SRX3436821 SRS2727765 SRP125961
## SRR6355995 PASS SRX3452604 SRS1802847 SRP126289
## SRR6369983 PASS SRX3465310 SRS2753257 SRP126582
## SRR6371359 PASS SRX3466682 SRS2754459 SRP126635
## SRR6464796 PASS SRX3554769 SRS2828122 SRP128927
## SRR6464797 PASS SRX3554769 SRS2828122 SRP128927
## SRR6464798 PASS SRX3554769 SRS2828122 SRP128927
## SRR6467601 PASS SRX3557548 SRS2830833 SRP129004
## SRR6467717 PASS SRX3557664 SRS2830946 SRP129004
## SRR6496863 PASS SRX3586008 SRS2854725 SRP131037
## SRR6503280 PASS SRX3591907 SRS2859986 SRP131149
## SRR6883165 PASS SRX3835409 SRS3082806 SRP136311
## SRR6926574 PASS SRX3872639 SRS3114043 SRP136938
## SRR6973585 PASS SRX3915416 SRS3151051 SRP139092
## SRR6978432 PASS SRX3919215 SRS3154204 SRP139334
## SRR7010505 PASS SRX3942984 SRS3173544 SRP140531
## SRR7011833 PASS SRX3944297 SRS3174833 SRP140558
## SRR7123448 PASS SRX4044517 SRS3261937 SRP144647
## SRR7130991 PASS SRX4051988 SRS3269027 SRP144905
## SRR7142047 PASS SRX4062867 SRS3279158 SRP145455
## SRR7236457 PASS SRX4142762 SRS3356559 SRP149366
## SRR7276093 PASS SRX4179700 SRS3391261 SRP149970
## SRR7293774 PASS SRX4196436 SRS3407070 SRP150311
## SRR7347194 PASS SRX4220595 SRS3421532 SRP150612
## SRR7478781 PASS SRX4348230 SRS3508075 SRP103099
## SRR7588317 PASS SRX4453577 SRS3592074 SRP155027
## SRR7889388 PASS SRX4726992 SRS3810537 SRP162329
## SRR7904770 PASS SRX4741212 SRS3822539 SRP162654
## SRR7908192 PASS SRX4744318 SRS3855914 SRP162735
## SRR7948181 PASS SRX4782130 SRS3862314 SRP163098
## SRR801695 PASS SRX258174 SRS406305 SRP020470
## SRR8528508 PASS SRX5331885 SRS4326230 SRP183532
## SRR8544036 PASS SRX5346149 SRS4337880 SRP184472
## SRR901189 PASS SRX306106 SRS445162 SRP026042
## SRR949076 PASS SRX332625 SRS468063 SRP028594
## SRR9652334 PASS SRX6413763 SRS5070852 SRP213631
## SRR9841092 PASS SRX6595812 SRS5161134 SRP216436
## SRR9874381 PASS SRX6627067 SRS5186602 SRP216966
## SRR9939088 PASS SRX6687653 SRS5245314 SRP217937
## Sample_name
## DRR017573 SAMD00009140
## DRR108715 SAMD00090951
## DRR109691 SAMD00092127
## DRR109692 SAMD00092128
## ERR1518673 SAMEA4065718
## ERR1594743 SAMEA3847037
## ERR1691932 SAMEA4514671
## ERR188129 SAMEA1573367
## ERR188184 SAMEA1573418
## ERR1910862 SAMEA103956351
## ERR1991839 SAMEA103885266
## ERR204924 SAMEA1573125
## ERR2059979 SAMEA104188614
## ERR2208954 SAMEA104411136
## ERR2303756 SAMEA104590897
## ERR2445954 SAMEA104718324
## ERR2619180 SAMEA4717818
## ERR2675483 SAMEA4766554
## ERR2700003 SAMEA4791453
## ERR3129937 SAMEA5280338
## ERR315411 SAMEA2147975
## ERR315466 SAMEA2151405
## ERR3299306 SAMEA5583174
## ERR3357674 SAMEA5693022
## ERR3490878 SAMEA5883846
## ERR576280 SAMEA2682058
## ERR752766 SAMEA3232299
## ERR752810 SAMEA3232313
## ERR866160 SAMEA3171879
## ERR973735 SAMEA3494652
## SRR10009502 GSM4041205
## SRR10068994 GSM4060364
## SRR10118992 GSM4079288
## SRR10143223 GSM4085033
## SRR10181297 GSM4095230
## SRR10259233 GSM4115622
## SRR10272816 GSM4119787
## SRR10353659 GSM4141729
## SRR10368246 GSM4144748
## SRR10446446 GSM4160405
## SRR10486655 GSM4174598
## SRR10505583 Z8
## SRR10581909 GSM4201703
## SRR10582374 GSM4202179
## SRR10604806 Exp6_HS746T_10nM
## SRR10620267 GSM4212789
## SRR10721014 GSM4222661
## SRR10741154 GSM4225682
## SRR10858280 GSM4257640
## SRR10858283 GSM4257643
## SRR11058878 GSM4305576
## SRR11058925 GSM4305640
## SRR11247856 GSM4386985
## SRR11247857 GSM4386985
## SRR11252261 GSM4392020
## SRR11290620 GSM4407382
## SRR11307901 HEK239T_RNA-seq_ABE8.17m-V106W_1
## SRR1146231 GSM1315768
## SRR11469900 NC_1_3h
## SRR11470749 GSM4451302
## SRR11542124 GSM4475898
## SRR11547440 1N
## SRR11548469 GSM4476834
## SRR11586961 GSM4490324
## SRR11615379 GSM4501055
## SRR11652607 GSM4506387
## SRR11780588 GSM4550436
## SRR11869905 RESCUE-S_rep2
## SRR1205933 mRNA-73
## SRR1272187 GSM1380719
## SRR1296129 GSM1396732
## SRR1448791 GSM1418974
## SRR1554437 GSM1482164
## SRR1576497 GSM1505847
## SRR1644195 GSM1540656
## SRR1702804 benchmark_Jurkat
## SRR1747214 GSM1580955
## SRR1777877 SCCOHT2
## SRR1947537 GSM1647005
## SRR2063343 GSM1712024
## SRR2099867 GSM1821002
## SRR2156107 HPGL0401
## SRR2313080 GSM1872068
## SRR2422379 GSM1885295
## SRR2481165 GSM1890714
## SRR2506915 Control 7
## SRR2761447 siMPLZ3_2
## SRR2970383 GSM1960716
## SRR3070185 GSM2024996
## SRR3192422 ENCODE biosample ENCBS088RNA
## SRR3213396 GSM2084200
## SRR3234008 GSM2092575
## SRR3362723 GSM2114350
## SRR3408051 GSM2130395
## SRR3471776 GSM2141391
## SRR3471926 GSM2141541
## SRR3503567 GSM2152538
## SRR3538912 GSM2157100
## SRR3644744 GSM2192672
## SRR3714679 GSM2212668
## SRR3885719 GSM2232085
## SRR3930018 GSM2241556
## SRR3932740 GSM2243023
## SRR3944326 GSM2248133
## SRR3954218 GSM2252997
## SRR3987797 GSM2256130
## SRR4007767 DMD1_Mt12
## SRR4113665 GSM2300451
## SRR4175280 NMC_cell_line_TY82
## SRR4240867 GSM2309640
## SRR4241352 GSM2309846
## SRR4255751 GSM2321864
## SRR4421980 ENCODE biosample ENCBS202CLF
## SRR4428773 GSM2350354
## SRR5032377 GSM2395561
## SRR5104192 GSM2427910
## SRR5118039 Hu8080
## SRR5124441 GSM2436466
## SRR5163544 GSM2451371
## SRR5185077 GSM2462065
## SRR5225467 GSM2475470
## SRR5225669 GSM2475672
## SRR5225767 GSM2475291
## SRR5236578 degraded.SEQC-A.5ng.rep2
## SRR5279123 GSM2500311
## SRR5305397 GSM2516926
## SRR5352626 GSM2539696
## SRR5352799 GSM2539869
## SRR542392 BR18
## SRR5444892 GSM2575400
## SRR5445642 GSM2576759
## SRR5488704 GSM2593195
## SRR5495045 GSM2596481
## SRR5528039 GSM2612489
## SRR5553974 GSM2627118
## SRR5559252 45Q-1-ESC
## SRR5676576 GSM2665632
## SRR5676577 GSM2665632
## SRR5750779 GSM2682879
## SRR5800692 GSM2692594
## SRR5802878 GSM2693234
## SRR5838317 GSM2706533
## SRR5862115 GSM2715792
## SRR5882130 C_80_RNA
## SRR5901932 GSM2733115
## SRR5902186 GSM2733369
## SRR5934783 GSM2742674
## SRR5981038 GSM2755110
## SRR5999449 GSM2770204
## SRR6000438 GSM2770728
## SRR6036044 GSM2784369
## SRR6050275 GSM2787456
## SRR6066217 GSM2791384
## SRR6149831 GSM2806812
## SRR6217804 GSM2830931
## SRR6217826 GSM2830955
## SRR6233791 P493-6, sCD40L (20ng/ml), a-IgM F(ab)2 fragments (26ng/ml), rhIGF-1 (100ng/ml), IL10 (5ng/ml)
## SRR6302566 GSM2860199
## SRR6337805 GSM2871851
## SRR6355995 GSM2392730
## SRR6369983 GSM2886127
## SRR6371359 GSM2886800
## SRR6464796 GSM2931827
## SRR6464797 GSM2931827
## SRR6464798 GSM2931827
## SRR6467601 GSM2932860
## SRR6467717 GSM2932976
## SRR6496863 GSM2942438
## SRR6503280 GSM2940525
## SRR6883165 GSM3061540
## SRR6926574 GSM3073430
## SRR6973585 GSM3090434
## SRR6978432 GSM3091270
## SRR7010505 GSM3099827
## SRR7011833 GSM3100368
## SRR7123448 GSM3131929
## SRR7130991 GSM3136673
## SRR7142047 GSM3138705
## SRR7236457 GSM3165463
## SRR7276093 GSM3178302
## SRR7293774 GSM3186685
## SRR7347194 PN-3
## SRR7478781 DFAB-92612-V0
## SRR7588317 GSM3305118
## SRR7889388 GSM3397819
## SRR7904770 GSM3402055
## SRR7908192 GSM3403196
## SRR7948181 Gene expression profiling in AuNP-treated MCF-7 cells
## SRR801695 GSM1111651
## SRR8528508 GSM3591007
## SRR8544036 GSM3593640
## SRR901189 GSM1163022
## SRR949076 GSM1203305
## SRR9652334 GSM3930435
## SRR9841092 GSM3978704
## SRR9874381 GSM3993271
## SRR9939088 GSM4024080
## GEO_series Library_name
## DRR017573 malaria8#12
## DRR108715 CRESTid1346
## DRR109691 CRESTid2426
## DRR109692 CRESTid2427
## ERR1518673 unspecified
## ERR1594743 16207243
## ERR1691932 b5_p
## ERR188129 NA19197.3.M_120202_2 extract
## ERR188184 NA19147.2.M_120131_2 extract
## ERR1910862 10380FJ0003L01
## ERR1991839 DN418836K:C3
## ERR204924 NA12045.1.M_120209_3 extract
## ERR2059979 unspecified
## ERR2208954 unspecified
## ERR2303756 Human-A017-patient-w13-2_p
## ERR2445954 Sample 6_s
## ERR2619180 HEPG2_3D_BR1_RNA_p
## ERR2675483 S8_normal_p
## ERR2700003 HGII_16293_1_p
## ERR3129937 TruSeq RNA Access
## ERR315411 V184
## ERR315466 V229
## ERR3299306 PR181_S21_p
## ERR3357674 TEC 5_s
## ERR3490878 Sample 305_p
## ERR576280 unspecified
## ERR752766 20PD01198
## ERR752810 20RD01346
## ERR866160 12655131
## ERR973735 MCF-7 untreated replicate 2
## SRR10009502 GSE136105
## SRR10068994 GSE136884
## SRR10118992 GSE137430
## SRR10143223 GSE137691
## SRR10181297 GSE137967
## SRR10259233 GSE138659
## SRR10272816 GSE138806
## SRR10353659 GSE139441
## SRR10368246 GSE139617
## SRR10446446 GSE140385
## SRR10486655 GSE138646
## SRR10505583 Z8
## SRR10581909 GSE141352
## SRR10582374 GSE141387
## SRR10604806 Exp6_HS746T_10nM
## SRR10620267 GSE141756
## SRR10721014 GSE142206
## SRR10741154 GSE142340
## SRR10858280 GSE143365
## SRR10858283 GSE143365
## SRR11058878 GSE145062
## SRR11058925 GSE145064
## SRR11247856 GSE146482
## SRR11247857 GSE146482
## SRR11252261 GSE146546
## SRR11290620 GSE146806
## SRR11307901 HEK239T_RNA-seq_ABE8.17m-V106W_1_L2
## SRR1146231
## SRR11469900 NC_1_3h
## SRR11470749 GSE147980
## SRR11542124 GSE148632
## SRR11547440 1
## SRR11548469 GSE148701
## SRR11586961 GSE149084
## SRR11615379 GSE149428
## SRR11652607 GSE149638
## SRR11780588 GSE150429
## SRR11869905 8
## SRR1205933 73-PE-IL7-1
## SRR1272187
## SRR1296129 GSE57896
## SRR1448791 GSE58740
## SRR1554437 GSE60548
## SRR1576497 GSE61476
## SRR1644195 GSE63086
## SRR1702804 hsa_rna_seq_rep_2_TRANSCRIPTOMIC
## SRR1747214 GSE64813
## SRR1777877
## SRR1947537 GSE67427
## SRR2063343 GSE69889
## SRR2099867 GSE70874
## SRR2156107 HPGL0401
## SRR2313080 GSE72790
## SRR2422379 GSE73092
## SRR2481165 GSE73318
## SRR2506915
## SRR2761447
## SRR2970383 GSE75627
## SRR3070185 GSE71812
## SRR3192422
## SRR3213396 GSE79029
## SRR3234008 GSE79338
## SRR3362723 GSE80183
## SRR3408051 GSE80537
## SRR3471776 GSE81046
## SRR3471926 GSE81046
## SRR3503567 GSE81439
## SRR3538912 GSE81550
## SRR3644744 GSE83083
## SRR3714679 GSE83687
## SRR3885719 GSE84337
## SRR3930018 GSE79843
## SRR3932740 GSE84620
## SRR3944326 GSE84712
## SRR3954218 GSE84877
## SRR3987797 GSE85011
## SRR4007767 DMD1_Mt12
## SRR4113665 GSE86337
## SRR4175280 TY_82_C5GJLACXX_TGACCA
## SRR4240867 GSE86356
## SRR4241352 GSE86884
## SRR4255751 GSE87080
## SRR4421980
## SRR4428773 GSE88858
## SRR5032377 GSE90014
## SRR5104192 GSE92346
## SRR5118039
## SRR5124441 GSE92723
## SRR5163544 GSE93326
## SRR5185077 GSE93783
## SRR5225467 GSE94438
## SRR5225669 GSE94438
## SRR5225767 GSE94437
## SRR5236578 LIB2
## SRR5279123 GSE95227
## SRR5305397 GSE95588
## SRR5352626 GSE96760
## SRR5352799 GSE96760
## SRR542392
## SRR5444892 GSE97681
## SRR5445642 GSE97744
## SRR5488704 GSE98386
## SRR5495045 GSE98454
## SRR5528039 GSE98812
## SRR5553974 GSE98894
## SRR5559252 45Q-1-ESC_fastq
## SRR5676576 GSE99944
## SRR5676577 GSE99944
## SRR5750779 GSE100427
## SRR5800692 GSE74180
## SRR5802878 GSE100785
## SRR5838317 GSE101595
## SRR5862115 GSE101794
## SRR5882130 LUSCLib_C-80_RNA
## SRR5901932 GSE102288
## SRR5902186 GSE102288
## SRR5934783 GSE102670
## SRR5981038 GSE103147
## SRR5999449 GSE103401
## SRR6000438 GSE103409
## SRR6036044 GSE103844
## SRR6050275 GSE103990
## SRR6066217 GSE104176
## SRR6149831 GSE104730
## SRR6217804 GSE106166
## SRR6217826 GSE106169
## SRR6233791 P493-6 combination 26
## SRR6302566 GSE107047
## SRR6337805 GSE107593
## SRR6355995 GSE89895
## SRR6369983 GSE107992
## SRR6371359 GSE108012
## SRR6464796 GSE109108
## SRR6464797 GSE109108
## SRR6464798 GSE109108
## SRR6467601 GSE109142
## SRR6467717 GSE109142
## SRR6496863 GSE109409
## SRR6503280 GSE109367
## SRR6883165 GSE112243
## SRR6926574 GSE112594
## SRR6973585 GSE112883
## SRR6978432 GSE112927
## SRR7010505 GSE113194
## SRR7011833 GSE113210
## SRR7123448 GSE114065
## SRR7130991 GSE114159
## SRR7142047 GSE114273
## SRR7236457 GSE115112
## SRR7276093 GSE115442
## SRR7293774 GSE115650
## SRR7347194 PN-3
## SRR7478781 DFAB-92612-V0
## SRR7588317 GSE117610
## SRR7889388 GSE120297
## SRR7904770 GSE120502
## SRR7908192 GSE120562
## SRR7948181 SAMN09976708
## SRR801695 GSE45669
## SRR8528508 GSE126078
## SRR8544036 GSE126207
## SRR901189 GSE47944
## SRR949076 GSE48173
## SRR9652334 GSE133942
## SRR9841092 GSE134908
## SRR9874381 GSE135192
## SRR9939088 GSE135635agg <- srx_agg(orgCountMetadata)
# Remove genes with zero total counts
length(which(rowSums(agg) == 0)) # 83## [1] 3746no_gene_counts <- names(which(rowSums(agg) == 0))
agg <- agg[!(rownames(agg) %in% no_gene_counts),]
# Save agg object
saveRDS(agg, "agg.rds")
# Histogram showing samples (columns) counts
hist(colSums(agg), breaks = 20)
# Remove unneeded data
remove(orgMetadata)6. Normalisation of Data (with PASS only databases)
# Filtering low counts
# Check if there are genes with no counts (rowSums==0)
length(which(rowSums(agg) == 0)) # no rowSums = 0## [1] 0#NORMALISATION FOR COMPOSITION BIAS (TMM normalisation)
dgeObj <- DGEList(agg)
# Apply TMM normalisation to DGEList object
dgeObj <- calcNormFactors(dgeObj, method = "TMM")
normAgg <- cpm(dgeObj)
# Scale after normalisation
normAggScale <- scale(normAgg)
# Check distributions of samples
hist(normAggScale)
saveRDS(normAggScale,"normAggScale.rds")
# Correlation Matrix
## memory error - need to fix
#correlate <- cor(t(normAggScale), method = "spearman")
#correlate[upper.tri(correlate,diag=TRUE)] <- NA
#correlate_melt <- melt(correlate, na.rm = TRUE)
#png("Data/hist_vds.png", width = 5*300, height = 5*300, res = 300, pointsize = 8)
#hist(correlate, breaks = 20, xlab = "Gene Correlation Values", main = "Spearman Correlation of RNASeq Counts")
#dev.off()
# Check for 0 values
#length(which(correlate_melt$value ==0 )) # no zero values7a. Hierarchical Clustering: linking method
There are different ways of deciding the distance of elements for them to be grouped into a cluster.The correlation between the distance matrix and the cophenetic distance is calculated to to ensure good linkage method fit.
set.seed(42)
distClust <-as.dist(1-cor(t(normAggScale), method="spearman"))
hClust <- hclust(distClust , method="complete")
# Check the correlation between the distance
# matrix and the cophenetic distance
cophenetic.d = cophenetic(hClust)
correlate_distClustVcoph <- cor(distClust, cophenetic.d)
png("Data/dendro_Average.png", width = 5*300, height = 5*300, res = 300, pointsize = 8)
dend <- as.dendrogram(hClust)
#labels_colors(dend) <- "white"
plot(dend, main = paste0("Complete Method: Corr = ", signif(correlate_distClustVcoph)))
dev.off()## png
## 27a.2 Data Removal
Removes data functions for memory storage
7b. Heirarchical Clustering: deciding the number of clusters
A specific number of clusters can be set using the cutree function.
# Using the argument k in cutree is a faster process vs
# figuring out the cut height
cutClust <- cutree(hClust, k=200)
cutClustlength <- length(unique(cutClust))
# Cluster size
cutClustlength## [1] 200# This is the base code used in the cl_lengthCut function below
clusters <- as.data.frame(cutClust)
colnames(clusters) <- "ClusterNumber"
clusters$GeneID <- rownames(clusters)8. Clustering genes using different cluster sizes
This functions will will yield a list of genes grouped in cluster sized of 50 to 2000 to be used in downstream processes.
leave eval=FALSE, code runs with difficulty (requires manual cutHeight addition)
# Different Cluster sizes using the normal dendrogram cutree function
cutClustvalues <- cl_lengthCut(hr=hClust, min=50, max=2000, interval=2)
saveRDS(cutClustvalues, "cutClustvalues.rds")
# Different Cluster sizes using the dynamic method, cutreeHybrid from the dynamicTreeCut library
cutClustvalues_dynamic <- cl_cut_dynamic(hr=hClust, cl=distClust, min=4, max=302, interval=2)## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.
## ..cutHeight not given, setting it to 1.88 ===> 99% of the (truncated) height range in dendro.
## ..done.saveRDS(cutClustvalues_dynamic, "cutClustvalues_dynamic.rds")9. Heatmaps for the clusters
NOT WORKING
# # Visualizations
# if (!exists("P100")){
# P100 <- createPalette(100, c("#ff0000", "#00ff00", "#0000ff"))}
#
# clusterCols <- P100[1:100]
# colfunc <- colorRampPalette(c("blue", "white", "red"))
#
# # Heatmaps TMM
# png("Data/hm_TMM_sp.png", width = 5*300, height = 5*300, res = 300, pointsize = 8)
# cutClustusterSideBar <- clusterCols[normAggCL_sp[["cutClust"]]]
# heatmap.2(corr, main="Gene Correlation (TMM, Spearman)", Rowv=as.dendrogram(hr),
# dendrogram="both", scale="col", col = colfunc(25), trace="none",
# RowSideColors= cutClustusterSideBar, margins = c(5,5))
# dev.off()10. Gene Ontology and Gene Data
A binary matrix was constructed with the Entrez Gene IDs (NCBI gene IDs) as rownames and GO IDs as the column names (wide format). If a GO ID is associated with a Gene ID, the cell will equal to 1, otherwise it will be zero.
Location for downloads: http://current.geneontology.org/products/pages/downloads.html
Will investigate using Ensembl BioMart.
# biomart
ensembl <- useEnsembl(biomart = "genes", dataset = "hsapiens_gene_ensembl")
orgGOlong <- getBM(
attributes=c("ensembl_gene_id","go_id"),
mart = ensembl)
orgGOlong <- orgGOlong[which(orgGOlong$go_id !="" ),]
# GO presence absence matrix
# gene ids in first column
# each row represents a gene (ENSG ID)
# each column represents a GO term eg GO:000002
orgGOmatrixwide <- cbind(orgGOlong[1], mtabulate(as.data.frame(t(orgGOlong[-1]))))
# Save the dataframe to an RDS file
saveRDS(orgGOmatrixwide, "orgGOmatrixwide.rds")
# GeneIDs that are in the gene count data but not in the GO matrix
diffCountGO <- setdiff(rownames(agg), orgGOmatrixwide$GeneID)
# GeneIDs that are in the GO matrix but not in the gene count data
diffGOCount <- setdiff(orgGOmatrixwide$GeneID, rownames(agg))
# Remove the GeneIDs that are in the GO matrix but not in the gene count data
IndexRemoved <- which(orgGOmatrixwide$GeneID %in% diffGOCount)
GOtable <- orgGOmatrixwide
GOtable <- GOtable[-IndexRemoved,]
# Check if the genes were properly removed
diffGOCount2 <- setdiff(GOtable$GeneID, rownames(agg))
dim(diffGOCount2)## NULL# Save the new GO table
saveRDS(GOtable, "GOtable.rds")
# Remove unneeded data
remove(orgGOlong)11. Blind GO Terms (90-10 split)
10 per cent of GeneIDs will have zero Gene Ontology Annotations. This will serve as the training data. After the model has been optimised, these IDs will be unblided as the testing data.
#Fraction of the total number of genes to be blinded
test_size <- floor(0.10 * nrow(GOtable))
## set the seed to make your partition reproducible
set.seed(42)
blinded_ind <- sample(seq_len(nrow(GOtable)), size = test_size)
GOtrain <- GOtable
GOtrain[blinded_ind, 2:ncol(GOtrain)] = 0
saveRDS(GOtrain, "GOtrain.rds")
GO_test <- GOtable[blinded_ind,]
saveRDS(GO_test, "GO_test.rds")
normAggScale_test <- normAggScale[rownames(normAggScale) %in% GO_test$GeneID,]
saveRDS(normAggScale_test, "normAggScale_test.rds")12. Data removal
Mem usage
sort( sapply( ls() , function(x) { object.size( get( x ) ) } ) )## diffGOCount diffGOCount2 blinded_ind
## 0 0 48
## IndexRemoved cutClustlength test_size
## 48 56 56
## totalPass qualitySummary databasePassList
## 56 1152 14232
## normAggScale_test GO_per_cl_list edge_list
## 14336 14408 15376
## qcPass corr_per_clust GO_per_cl
## 19032 19040 23168
## mean_Csweep GO_per_cl_blinded summary_Csweep
## 23344 23448 27360
## optimise_impute wcorr_cluster cross_val
## 29472 30024 35736
## cross_val_thresh stats_all stats_cl
## 36000 54040 67592
## orgMetadataPass impute cl_lengthCut
## 86992 100656 160192
## srx_agg cl_cut_dynamic no_gene_counts
## 169184 171024 269760
## ensembl qcData GO_test
## 1375616 1657992 2429528
## GOtable GOtrain diffCountGO
## 2429528 2429528 3928080
## cutClust hClust clusters
## 4146464 5021088 8075136
## orgPassWide orgCountMetadata agg
## 50165536 50252896 88176880
## normAgg dgeObj normAggScale
## 88176880 88196880 88208400
## cutClustvalues_dynamic cutClustvalues distClust
## 362211544 7950375184 11909140528
## orgGOmatrixwide
## 30635520592Session Information
## R version 4.0.1 (2020-06-06)
## Platform: x86_64-conda_cos6-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.3 LTS
##
## Matrix products: default
## BLAS/LAPACK: /ceph-g/opt/miniconda3/envs/R40/lib/libopenblasp-r0.3.9.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] parallel stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] qdapTools_1.3.5 biomaRt_2.44.4
## [3] dynamicTreeCut_1.63-1 DESeq2_1.28.1
## [5] SummarizedExperiment_1.18.2 DelayedArray_0.14.1
## [7] matrixStats_0.61.0 Biobase_2.48.0
## [9] GenomicRanges_1.40.0 GenomeInfoDb_1.24.2
## [11] IRanges_2.22.2 S4Vectors_0.26.1
## [13] BiocGenerics_0.34.0 ggplot2_3.3.5
## [15] dendextend_1.15.2 Polychrome_1.3.1
## [17] reshape2_1.4.4 edgeR_3.30.3
## [19] limma_3.44.3 gplots_3.1.1
## [21] RColorBrewer_1.1-2 data.table_1.12.8
## [23] tidyr_1.1.0 dplyr_1.0.8
## [25] R.utils_2.11.0 R.oo_1.24.0
## [27] R.methodsS3_1.8.1
##
## loaded via a namespace (and not attached):
## [1] bitops_1.0-7 bit64_4.0.5 httr_1.4.1
## [4] progress_1.2.2 tools_4.0.1 utf8_1.1.4
## [7] R6_2.4.1 KernSmooth_2.23-17 DBI_1.1.0
## [10] colorspace_1.4-1 withr_2.2.0 prettyunits_1.1.1
## [13] tidyselect_1.1.1 gridExtra_2.3 chron_2.3-56
## [16] curl_4.3 bit_4.0.4 compiler_4.0.1
## [19] cli_3.1.1 xml2_1.3.2 caTools_1.18.2
## [22] scales_1.1.1 genefilter_1.70.0 askpass_1.1
## [25] rappdirs_0.3.3 stringr_1.4.0 digest_0.6.25
## [28] rmarkdown_2.3 XVector_0.28.0 pkgconfig_2.0.3
## [31] htmltools_0.5.0 dbplyr_1.4.4 fastmap_1.0.1
## [34] rlang_1.0.0 RSQLite_2.2.9 generics_0.0.2
## [37] BiocParallel_1.22.0 gtools_3.9.2 RCurl_1.98-1.5
## [40] magrittr_1.5 GenomeInfoDbData_1.2.3 Matrix_1.2-18
## [43] Rcpp_1.0.8 munsell_0.5.0 fansi_0.4.1
## [46] viridis_0.5.1 lifecycle_1.0.1 scatterplot3d_0.3-41
## [49] stringi_1.4.6 yaml_2.2.1 zlibbioc_1.34.0
## [52] BiocFileCache_1.12.1 plyr_1.8.6 grid_4.0.1
## [55] blob_1.2.1 crayon_1.3.4 lattice_0.20-41
## [58] splines_4.0.1 annotate_1.66.0 hms_0.5.3
## [61] locfit_1.5-9.4 knitr_1.28 pillar_1.7.0
## [64] geneplotter_1.66.0 XML_3.99-0.8 glue_1.4.1
## [67] evaluate_0.14 vctrs_0.3.8 openssl_1.4.1
## [70] gtable_0.3.0 purrr_0.3.4 assertthat_0.2.1
## [73] cachem_1.0.6 xfun_0.15 xtable_1.8-4
## [76] survival_3.2-3 viridisLite_0.3.0 tibble_3.0.1
## [79] AnnotationDbi_1.50.3 memoise_2.0.1 ellipsis_0.3.2