Visualize three-way paired interaction

Question

I have a dataframe of information regarding a list of "tri-complexes" or "triplets" which comprise probeID, target_symbol, and TF_symbol.

The "desired output" fulfills the aforementioned goal. However, it does not capture the interaction between specific interactions between the "triplets".

Furthermore, a traceback is raised because the nrow of distal.dmr.cpgs is based on the number of triplets, whereas the number of rows in t(met) and t(exp) are based on the total number of samples. I want to capture all the triplets.

Aside from the desired output, I'm also considering correlation heatmap or 2D density plot.

Data processing:

library(EnrichedHeatmap)
library(GetoptLong)
library(circlize)
library(RColorBrewer)
library(ComplexHeatmap)
library(ELMER)
library(MultiAssayExperiment)
library(MOVICS)
library(matrixStats)
library(GenomicRanges)
library(IlluminaHumanMethylation450kanno.ilmn12.hg19)
library(caret)
library(mlbench)
library(dendsort)
library(dendextend)
library(dplyr)
library(tidyr)
library(gridBase)

sample.hyper <- data.frame(matrix(ncol=1, nrow=nrow(bval.tn.hyper)))
rownames(sample.hyper) <- rownames(bval.tn.hyper)
colnames(sample.hyper) <- "dirct"
sample.hyper["dirct"] <- "hyper"
sample.hypo <- data.frame(matrix(ncol=1, nrow=nrow(bval.tn.hypo)))
rownames(sample.hypo) <- rownames(bval.tn.hypo)
colnames(sample.hypo) <- "dirct"
sample.hypo["dirct"] <- "hypo"
sample <- rbind(sample.hyper, sample.hypo)
direction <- c(sample$dirct)

cor.meth.pvalue <- distal.dmr.cpgs$RLM_DNAmGroup_pvalue
cor.tf.pvalue <- distal.dmr.cpgs$RLM_TF_pvalue
cor.meth.tf.synergistic.pvalue <- distal.dmr.cpgs$`RLM_DNAmGroup:TF_pvalue`

dist <- distal.dmr.cpgs$distance_region_target_tss

Heatmap:

# Split by subtype category
split <- clin.info$subtype
sectors <- unique(split)
s1 <- factor(sectors)

# Colors
col.meth <-colorRamp2(c(-2, 0, 2), c("#00539C", "#f1f1f1", "#EEA47F"))
col.expr <- colorRamp2(c(-2, 0, 2), c("#317773", "#f1f1f1", "#E2D1F9"))
col.dnam.effect <- c("Attenuating"="#EC449B", "Enhancing"="#99F443", "ns"="#f1f1f1")
col.tf.role <- c("Repressor"="#CCF381", "Activator"="#4831D4", "ns"="#f1f1f1")
col.dnam.pval <- colorRamp2(c(-2, 0, 2), c("#f1f1f1", "#ffa3cf", "#FF69B4")) # for results.stratified.model
col.TF.pval <- colorRamp2(c(-2, 0, 2), c("#f1f1f1", "#EED971", "#FFA351")) # for results.stratified.model
col.synergistic.dnam.tf.pval <- colorRamp2(c(-2, 0, 2), c("#8A307F", "white", "#6883BC")) # for results.stratified.model
col.dist <- colorRamp2(c(0, 5000, 10000), c("#00FFFF", "#b1eeec", "#f1f1f1"))

circlize_plot = function() {
  circos.heatmap(t(met), col=col.meth, track.height=0.12, split=split)
  circos.heatmap(distal.dmr.cpgs$DNAm.effect, col=col.dnam.effect, track.height=0.01)
  circos.heatmap(distal.dmr.cpgs$TF.role, col=col.tf.role, track.height=0.01)
  circos.heatmap(t(exp), col=col.expr, track.height=0.12)
  circos.heatmap(cor.meth.pvalue, col=col.dnam.pval, track.height=0.01)
  circos.heatmap(cor.tf.pvalue, col=col.TF.pval, track.height=0.01)
  circos.heatmap(cor.meth.tf.synergistic.pvalue, col=col.synergistic.dnam.tf.pval, track.height=0.01)
  circos.heatmap(dist, col=col.dist, track.height = 0.01)
  circos.clear()
}

# Labels
labels <- paste0(distal.dmr.cpgs$target_symbol,":",distal.dmr.cpgs$probeID)

# Legends
#lgd.subtype <- Legend(title="Subtype", legend_gp=gpar(fill=clust.col), at=names(clust.col))
lgd.meth <- Legend(title="Methylation", col_fun=col.meth)
lgd.expr <- Legend(title="Expression", col_fun=col.expr)
lgd.dnam.effect <- Legend(title="DNAm effect", at=names(col.dnam.effect), legend_gp=gpar(fill=col.dnam.effect))
lgd.tf.role <- Legend(title="TF role", at=names(col.tf.role), legend_gp=gpar(fill=col.tf.role))
lgd.dnam.pval <- Legend(title="DNAm P-value", col_fun=col.dnam.pval, at=c(0, 2, 4), labels=c(1, 0.01, 0.0001))
lgd.TF.pval <- Legend(title="TF P-value", col_fun=col.TF.pval, at=c(0, 2, 4), labels=c(1, 0.01, 0.0001))
lgd.synergistic.dnam.tf.pval <- Legend(title="Synergistic DNAm-TF P-value", col_fun=col.synergistic.dnam.tf.pval, at=c(0, 2, 4), labels=c(1, 0.01, 0.0001))
lgd.dist <- Legend(title="Dist to TSS", col_fun=col.dist, at=c(0, 5000, 10000), labels=c("0kb", "5kb", "10kb"))

pdf("Plots/KIRP_circular_correlation_meth_exp_heatmap_methreg.pdf")
plot.new()
circle.size = unit(1, "snpc")
pushViewport(viewport(x = 0, y = 0.5, width = circle.size, height = circle.size,
                      just = c("left", "center")))
par(omi = gridOMI(), new = TRUE)
circlize_plot()
upViewport()
h = dev.size()[2]
lgd.list = packLegend(lgd.meth, lgd.expr, lgd.dnam.effect, lgd.tf.role, lgd.dnam.pval, lgd.TF.pval, lgd.synergistic.dnam.tf.pval, lgd.dist,
                      max_height=unit(0.9*h, "inch"))
draw(lgd.list, x=circle.size, just="left")
circos.labels(sectors=split, labels=labels, niceFacing=T, side="outside", x=0.5)

Traceback:

Error in `[[<-.data.frame`(`*tmp*`, 4, value = c("SRRM2:cg03477043", "SRRM2:cg03477043",  : 
  replacement has 197 rows, data has 202

Visualization for a single gene-TF-CpG "triplet".

Desired output:

Sample input:

> dput(distal.dmr.cpgs[1:20,])
structure(list(regionID = c("chr16:2762422-2762423", "chr16:2762422-2762423", 
"chr16:89379025-89379026", "chr16:89379025-89379026", "chr16:89379025-89379026", 
"chr16:89379025-89379026", "chr16:89379095-89379096", "chr16:89379095-89379096", 
"chr16:89379095-89379096", "chr16:89379095-89379096", "chr16:89379095-89379096", 
"chr17:77319786-77319787", "chr17:80891955-80891956", "chr17:80891955-80891956", 
"chr17:80891955-80891956", "chr17:80891955-80891956", "chr14:102219341-102219342", 
"chr14:102219341-102219342", "chr1:2372936-2372937", "chr1:2372936-2372937"
), probeID = c("cg03477043", "cg03477043", "cg00926926", "cg00926926", 
"cg00926926", "cg00926926", "cg00488747", "cg00488747", "cg00488747", 
"cg00488747", "cg00488747", "cg04452095", "cg04658243", "cg04658243", 
"cg04658243", "cg04658243", "cg07156990", "cg07156990", "cg01520454", 
"cg01520454"), target = c("ENSG00000167978", "ENSG00000167978", 
"ENSG00000167522", "ENSG00000167522", "ENSG00000167522", "ENSG00000167522", 
"ENSG00000167522", "ENSG00000167522", "ENSG00000167522", "ENSG00000167522", 
"ENSG00000167522", "ENSG00000184640", "ENSG00000141564", "ENSG00000141564", 
"ENSG00000141564", "ENSG00000141564", "ENSG00000080824", "ENSG00000080824", 
"ENSG00000157916", "ENSG00000157916"), target_symbol = c("SRRM2", 
"SRRM2", "ANKRD11", "ANKRD11", "ANKRD11", "ANKRD11", "ANKRD11", 
"ANKRD11", "ANKRD11", "ANKRD11", "ANKRD11", "SEPTIN9", "RPTOR", 
"RPTOR", "RPTOR", "RPTOR", "HSP90AA1", "HSP90AA1", "RER1", "RER1"
), TF_symbol = c("CTCF", "CREB3", "RELA", "ZNF384", "NFYC", "FOXK2", 
"RELA", "STAT3", "ZNF384", "NFYC", "FOXK2", "STAT3", "CTCF", 
"STAT3", "ZNF317", "FOXK2", "ZNF317", "E2F4", "RELA", "CTCF"), 
    TF = c("ENSG00000102974", "ENSG00000107175", "ENSG00000173039", 
    "ENSG00000126746", "ENSG00000066136", "ENSG00000141568", 
    "ENSG00000173039", "ENSG00000168610", "ENSG00000126746", 
    "ENSG00000066136", "ENSG00000141568", "ENSG00000168610", 
    "ENSG00000102974", "ENSG00000168610", "ENSG00000130803", 
    "ENSG00000141568", "ENSG00000130803", "ENSG00000205250", 
    "ENSG00000173039", "ENSG00000102974"), distance_region_target_tss = c(9795, 
    9795, 111534, 111534, 111534, 111534, 111464, 111464, 111464, 
    111464, 111464, 39216, 347135, 347135, 347135, 347135, -79641, 
    -79641, -18837, -18837), target_region = c("chr16:2752626-2772538", 
    "chr16:2752626-2772538", "chr16:89267630-89490561", "chr16:89267630-89490561", 
    "chr16:89267630-89490561", "chr16:89267630-89490561", "chr16:89267630-89490561", 
    "chr16:89267630-89490561", "chr16:89267630-89490561", "chr16:89267630-89490561", 
    "chr16:89267630-89490561", "chr17:77280569-77500596", "chr17:80544819-80966371", 
    "chr17:80544819-80966371", "chr17:80544819-80966371", "chr17:80544819-80966371", 
    "chr14:102080742-102139699", "chr14:102080742-102139699", 
    "chr1:2391775-2405442", "chr1:2391775-2405442"), met.IQR = c(0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), 
    RLM_DNAmGroup_pvalue = c(0.0422464065351595, 0.0344133919449146, 
    0.0473017788132601, 0.0484196210021861, 0.0435840226150332, 
    0.0308252756419765, 0.00150201162815966, 0.00151985887265838, 
    0.00275663535734938, 0.0012627667435956, 0.000430707563700894, 
    0.0657700026882084, 0.0347366442479191, 0.0211072874435114, 
    0.0256069513155897, 0.0217420274661757, 0.00988389189390837, 
    0.00457206277555011, 0.00701145653446389, 0.226393179149396
    ), RLM_DNAmGroup_fdr = c(0.0422464065351595, 0.0422464065351595, 
    0.0484196210021861, 0.0484196210021861, 0.0484196210021861, 
    0.0484196210021861, 0.00189982359082297, 0.00189982359082297, 
    0.00275663535734938, 0.00189982359082297, 0.00189982359082297, 
    0.0657700026882084, 0.0434208053098989, 0.0426782521926494, 
    0.0426782521926494, 0.0426782521926494, 0.0296516756817251, 
    0.0274323766533007, 0.0350572826723194, 0.226393179149396
    ), RLM_TF_pvalue = c(0.0419750640980108, 0.0103671579957865, 
    0.467132225063278, 0.72093859766613, 0.272092275972533, 0.000514794320566114, 
    0.891428521530259, 0.853872726027603, 0.161356975335507, 
    0.823791465863571, 0.0205784261111761, 0.000128646537908228, 
    0.205975758470008, 0.0962600130713416, 0.0172923281979998, 
    3.55524281125952e-07, 0.40404615170336, 0.680751491377743, 
    0.010686329872216, 2.22866863497373e-06), RLM_TF_fdr = c(0.0419750640980108, 
    0.0207343159915729, 0.622842966751037, 0.72093859766613, 
    0.544184551945066, 0.00205917728226446, 0.891428521530259, 
    0.891428521530259, 0.403392438338768, 0.891428521530259, 
    0.102892130555881, 0.000128646537908228, 0.25746969808751, 
    0.160433355118903, 0.0432308204949994, 1.77762140562976e-06, 
    0.60606922755504, 0.680751491377743, 0.010686329872216, 5.57167158743432e-06
    ), `RLM_DNAmGroup:TF_pvalue` = c(0.816616675064483, 0.315518615926782, 
    0.334800389930188, 0.886558336903593, 0.288111456068547, 
    0.0553116797875954, 0.674629382494593, 0.611101293078096, 
    0.82494221468516, 0.601335599655604, 0.46488686635087, 0.827720937109957, 
    0.264038157296601, 0.847940571174651, 0.251439830868016, 
    0.410065594864625, 0.970959624372413, 0.933961574502706, 
    0.382832592641406, 0.0520128501668689), `RLM_DNAmGroup:TF_fdr` = c(0.816616675064483, 
    0.631037231853565, 0.446400519906918, 0.886558336903593, 
    0.446400519906918, 0.221246719150382, 0.82494221468516, 0.82494221468516, 
    0.82494221468516, 0.82494221468516, 0.82494221468516, 0.827720937109957, 
    0.660095393241502, 0.847940571174651, 0.660095393241502, 
    0.683442658107708, 0.970959624372413, 0.970959624372413, 
    0.478540740801758, 0.0949432659778482), RLM_DNAmGroup_estimate = c(0.391366841432446, 
    0.371327086133833, 0.395884100676198, 0.390536544990631, 
    0.40695391264101, 0.408579807600067, 0.70307776267823, 0.706552565374348, 
    0.649042588677745, 0.721190519859083, 0.747413814733246, 
    0.329800594180331, 0.386973136345643, 0.404763286514642, 
    0.404447228425067, 0.345633742019318, 0.498591859282836, 
    0.556780839784354, -0.607415817481504, -0.251450099432731
    ), RLM_TF_estimate = c(0.281227589928979, -0.323039230805149, 
    -0.110519428773639, 0.0548209506490028, 0.162772915125468, 
    0.463202502783608, -0.0212827073929813, -0.0295766095061422, 
    0.195192883961314, 0.0369136296170289, 0.308005451059777, 
    0.514331784588719, 0.185059618725655, 0.207865845912526, 
    -0.288065323365035, 0.507552983467692, 0.116124939897262, 
    0.0507547278489005, 0.395036883763581, -0.59881856261158), 
    `RLM_DNAmGroup:TF_estimate` = c(0.0476365755291261, -0.165727596247364, 
    0.203133492532222, 0.0292733545380043, -0.216456686525197, 
    -0.356607795519526, 0.0847642614797746, 0.109600973249801, 
    -0.0437870163085532, 0.115542672949099, -0.132156021604734, 
    -0.0371847139216182, -0.206182842706317, 0.0323853811860214, 
    0.194922003418853, -0.117263827755975, -0.0069793158180777, 
    -0.0151825142848314, -0.178861319734404, 0.380231815730904
    ), Model.quantile = c("Robust Linear Model", "Robust Linear Model", 
    "Robust Linear Model", "Robust Linear Model", "Robust Linear Model", 
    "Robust Linear Model", "Robust Linear Model", "Robust Linear Model", 
    "Robust Linear Model", "Robust Linear Model", "Robust Linear Model", 
    "Robust Linear Model", "Robust Linear Model", "Robust Linear Model", 
    "Robust Linear Model", "Robust Linear Model", "Robust Linear Model", 
    "Robust Linear Model", "Robust Linear Model", "Robust Linear Model"
    ), Target_gene_DNAm_high_vs_Target_gene_DNAm_low_wilcoxon_pvalue = c(0.0111947515949219, 
    0.0111947515949219, 0.02969053900481, 0.02969053900481, 0.02969053900481, 
    0.02969053900481, 0.00113717643198146, 0.00113717643198146, 
    0.00113717643198146, 0.00113717643198146, 0.00113717643198146, 
    0.0348370428272982, 0.0428689068203914, 0.0428689068203914, 
    0.0428689068203914, 0.0428689068203914, 0.00693436508157953, 
    0.00693436508157953, 0.0128889269825682, 0.0128889269825682
    ), TF_DNAm_high_vs_TF_DNAm_low_wilcoxon_pvalue = c(0.417943629363925, 
    0.135674453768463, 0.145235627143256, 0.680264511884829, 
    0.113088638511403, 0.926405872904368, 0.417943629363925, 
    0.560144252514798, 0.495175592310321, 0.179309287244037, 
    0.235397217999978, 0.517907592230554, 0.675064552437567, 
    0.333889773574117, 0.527149228657931, 0.759967056390364, 
    0.130175590812792, 0.252648984550288, 0.490694010679184, 
    0.00609528020425919), `% of target genes not expressed in DNAm_low and DNAm_high` = c("0 %", 
    "0 %", "0 %", "0 %", "0 %", "0 %", "0 %", "0 %", "0 %", "0 %", 
    "0 %", "0 %", "0 %", "0 %", "0 %", "0 %", "0 %", "0 %", "0 %", 
    "0 %"), DNAm_low_RLM_target_vs_TF_pvalue = c(0.0259364958125814, 
    0.00753553623999004, 0.460325106599497, 0.692693342638731, 
    0.315289731003607, 0.000756745896691946, 0.892812259055557, 
    0.850393817987769, 0.137294538551965, 0.813640144669246, 
    0.0164842214523691, 0.00013431112038309, 0.250732764175728, 
    0.154672455522276, 0.0246355132162588, 2.86542930405531e-06, 
    0.504696888913462, 0.823663796298662, 0.0546699590738258, 
    7.8307879803452e-05), DNAm_low_RLM_target_vs_TF_estimate = c(0.27906988386453, 
    -0.323013805407332, -0.118743186892688, 0.0640624351376578, 
    0.158695080628396, 0.460733657087822, -0.020838062194407, 
    -0.0301913231291102, 0.206016183618269, 0.038783711513423, 
    0.316818199925549, 0.514138781448701, 0.189162534005193, 
    0.205796338803218, -0.307087001296972, 0.512219526190152, 
    0.0983423103315685, 0.0292961114629098, 0.359196382006078, 
    -0.585550908482295), DNAm_high_RLM_target_vs_TF_pvalue = c(0.0527939209600978, 
    0.000106204477959615, 0.493175812986649, 0.514588360117673, 
    0.728135657907864, 0.422326547532424, 0.632621266523826, 
    0.585265337302442, 0.302558584728815, 0.297918126183749, 
    0.177793604237108, 0.000106669732659936, 0.834014823903555, 
    0.0214981308608362, 0.416088474233892, 0.000520719223967125, 
    0.351511466191903, 0.722047286187858, 0.0375438142474882, 
    0.0902696872889863), DNAm_high_RLM_target_vs_TF_estimate = c(0.333610936801836, 
    -0.488728802926698, 0.0951631917249828, 0.0845092162375904, 
    -0.0460710731343046, 0.106818566360051, 0.0621604325281235, 
    0.0796459855690455, 0.149478480439067, 0.152745219994597, 
    0.175250167646223, 0.480661113612985, -0.0214535251073133, 
    0.240724084860221, -0.0899708442825302, 0.390759450029979, 
    0.116452979831903, 0.044106133569431, 0.223658983484041, 
    -0.232819952842701), DNAm.effect = c("ns", "ns", "ns", "ns", 
    "ns", "ns", "ns", "ns", "ns", "ns", "ns", "ns", "ns", "ns", 
    "ns", "ns", "ns", "ns", "ns", "ns"), TF.role = c("ns", "Repressor", 
    "ns", "ns", "ns", "Activator", "ns", "ns", "ns", "ns", "ns", 
    "Activator", "ns", "ns", "ns", "Activator", "ns", "ns", "ns", 
    "Repressor"), cpg_type = c("distal", "distal", "distal", 
    "distal", "distal", "distal", "distal", "distal", "distal", 
    "distal", "distal", "distal", "distal", "distal", "distal", 
    "distal", "distal", "distal", "distal", "distal")), row.names = c(785L, 
786L, 866L, 867L, 868L, 869L, 870L, 871L, 872L, 873L, 874L, 955L, 
991L, 992L, 993L, 994L, 1541L, 1542L, 1684L, 1685L), class = "data.frame")

> dput(met[1:10,1:10])
structure(c(0.0963816428247783, 0.264597521491571, 0.0900208830548926, 
0.0302926578812254, 0.116720581216524, 0.110392765501207, 0.0544351533038203, 
0.0389795102004534, 0.147765926780052, 0.679689366786141, 0.0815254902491508, 
0.19559084049603, 0.334755512389145, 0.0484924457346441, 0.282282576723208, 
0.165918840293871, 0.0202491526169829, 0.0401063058709833, 0.196427892836785, 
0.19541766960863, 0.319094380796508, 0.356903638301111, 0.373155103913411, 
0.099029945170814, 0.232482124616956, 0.111926430647544, 0.411717334407087, 
0.445579348397267, 0.336824020289618, 0.586726487767714, 0.0545596258768511, 
0.239765234403304, 0.728876917156836, 0.0664945125887669, 0.118660689268703, 
0.0440951608387592, 0.0212735236078356, 0.0357010500308833, 0.338572152832189, 
0.246246327929496, 0.103903782463444, 0.337642646237331, 0.114420995265166, 
0.0641810918774967, 0.0981564968977369, 0.0937765297459675, 0.0349132573096255, 
0.0357266286504234, 0.101064830492531, 0.657158733098722, 0.08980490874764, 
0.303020929992783, 0.0912579245912579, 0.118426501035197, 0.0997325336359215, 
0.40254877063373, 0.0705802405008416, 0.0407359941413402, 0.169829778908237, 
0.697879155713287, 0.0573797900086939, 0.167782591571485, 0.0314559616536848, 
0.0433534309503302, 0.133653012294037, 0.345830639948287, 0.0343027098479841, 
0.0279712163416899, 0.042737461791011, 0.364642737336464, 0.138945883559887, 
0.31703056768559, 0.428923677925293, 0.0648533786655334, 0.173653083772015, 
0.0941069900860551, 0.0185242087704666, 0.0614764298870028, 0.117584520518818, 
0.395478537994224, 0.129856471170502, 0.265259409969481, 0.567530471066213, 
0.0897088397306986, 0.221332328276642, 0.0607481615687946, 0.0578740240335038, 
0.0580142703912699, 0.10219285915097, 0.690333919156415, 0.185606060606061, 
0.267122572562122, 0.501743395780391, 0.339076334051208, 0.218889644453079, 
0.117934986682201, 0.0807086614173228, 0.0985031033223804, 0.0864774971416693, 
0.617845692066307), dim = c(10L, 10L), dimnames = list(c("cg00008647", 
"cg00027570", "cg00044796", "cg00065215", "cg00065905", "cg00069860", 
"cg00114029", "cg00151709", "cg00155063", "cg00172603"), c("TCGA.Y8.A8S1.01", 
"TCGA.Y8.A8S0.01", "TCGA.Y8.A8RZ.01", "TCGA.Y8.A8RY.01", "TCGA.Y8.A897.01", 
"TCGA.Y8.A896.01", "TCGA.Y8.A895.01", "TCGA.Y8.A894.01", "TCGA.WN.A9G9.01", 
"TCGA.V9.A7HT.01")))

> dput(exp[1:10,1:10])
structure(list(TCGA.2K.A9WE.01 = c(7.65342121905285, 14.3511850042327, 
10.3737643425674, 10.0819596419255, 9.44832324553208, 5.36085937172008, 
10.3776687573505, 11.16757118884, 9.53872845925388, 9.59256168492636
), TCGA.2Z.A9J1.01 = c(5.09389393824392, 12.4136523086721, 11.1918237390263, 
10.1912122382252, 9.9623840324273, 6.22565668754941, 10.3103072842012, 
11.1287210937383, 9.12552428380532, 10.0220514952103), TCGA.2Z.A9J3.01 = c(4.70168212029528, 
10.1689338100564, 9.96839262629172, 9.87305770150294, 9.75535162798678, 
6.170389794965, 9.94050095178643, 11.0690397931313, 9.18120494347434, 
10.1026705963882), TCGA.2Z.A9J5.01 = c(7.99645936536463, 13.6832285748428, 
10.3714563849361, 10.4176870383992, 10.0652444551968, 5.98935248863472, 
11.2050505161752, 11.6645692817891, 9.14131578384568, 10.4504026669882
), TCGA.2Z.A9J6.01 = c(5.13719199914349, 12.0367193976262, 10.8202555636581, 
10.3262700402849, 9.91216810777653, 5.52284042813955, 10.5954686012028, 
11.2355920880251, 9.10909645558853, 9.94472260124272), TCGA.2Z.A9J7.01 = c(6.95117512427229, 
10.9656928148969, 10.5991523452113, 10.4556415168452, 9.46537845450025, 
6.72337288854289, 9.28408724134641, 11.4833270722276, 9.49617650025352, 
10.4425557194467), TCGA.2Z.A9J8.01 = c(3.61712213221935, 11.9975977242282, 
9.91379851626213, 9.95999222715916, 9.90779350021794, 7.85831302551685, 
11.7402171909708, 11.7246448152361, 9.75167259046219, 9.68598603763708
), TCGA.2Z.A9JD.01 = c(3.15639661659767, 10.9506421354115, 10.8015070949819, 
9.51027580369917, 10.0114476969219, 5.9232585434528, 10.9093204661635, 
11.1601119970792, 9.35889972298825, 9.89445931817658), TCGA.2Z.A9JI.01 = c(8.20162111992077, 
12.7954861179578, 10.0094938620897, 9.93400880935778, 9.75330735360058, 
7.0082672553098, 10.7382235152475, 11.6720072357516, 8.44494819471576, 
9.99223068991282), TCGA.2Z.A9JJ.01 = c(6.26475409489153, 12.8198023802381, 
11.7916439373724, 9.53606689182685, 10.3591574288036, 5.71406413888836, 
10.2195932783632, 11.455724780085, 8.42239448735832, 9.24745049099849
)), row.names = c("A1BG", "A2M", "A4GALT", "AAAS", "AACS", "AADAT", 
"AAK1", "AAMP", "AARS2", "AARSD1"), class = "data.frame")