CNVscan for SRP199233

Intro

Here we’re doing an analysis to identify CNV using normalised reads counts across genomic windows.

library("cobs")
library("quantreg")
library("parallel")
library("gplots")
library("dplyr")
library("kableExtra")

interpolate_points<-function(row,dat,curve){
  MY_X=dat[row,1]
  MY_Y=dat[row,2]
  VAL1=tail(which(curve[,1]<MY_X),1)
  VAL2=VAL1+1
  X <- curve[c(VAL1,VAL2),1]
  Y <- curve[c(VAL1,VAL2),2]
  INTERP_Y=approx(X,Y,xout=MY_X)$y
  INTERP_Y
}

1 Mbp bins

x <- read.table("SRP199233.1e6_fmt.tsv",header=T,row.names=1)
x <- x[which(rowSums(x)>=10),]
x <- sweep(x, 2, colSums(x), FUN="/")*1000000
mysd <- apply(x,1,sd)
mean <- apply(x,1,mean)
y <- data.frame(log10(mean),mysd/mean)
colnames(y) <- c("logMean","cv")
Rbs.9 <- cobs(y$logMean,y$cv, nknots=10,constraint="none",tau=0.99)

## qbsks2():
##  Performing general knot selection ...
## 
##  WARNING! Since the number of  10  knots selected by  AIC  reached the
##    upper bound during general knot selection, you might want to rerun
##    cobs with a larger number of knots. 
## 
##  Deleting unnecessary knots ...
## 
##  WARNING! Since the number of  10  knots selected by  AIC  reached the
##    upper bound during general knot selection, you might want to rerun
##    cobs with a larger number of knots.

Rbs.median <- cobs(y$logMean,y$cv,nknots=10,constraint="none",tau=0.5)

## qbsks2():
##  Performing general knot selection ...
## 
##  Deleting unnecessary knots ...

pred <- data.frame(predict(Rbs.9))

res <- mclapply(X=1:nrow(y),function(row) {
  interpolate_points(row,y,pred)
  },mc.cores=8)
y$interpolated <- unlist(res)

y$diff <-  y$cv-y$interpolated
yy <- y[order(-y$diff),]
yy <- head(yy,50)

write.table(yy,file="SRP199233.1e6_regions.tsv")

yy %>% kbl() %>% kable_paper("hover", full_width = F)

	logMean	cv	interpolated	diff
9:124000000-124359700	2.0390327	0.1537191	0.1289709	0.0247482
MT:0-16299	1.6161335	0.2641279	0.2498461	0.0142818
MU069435.1:0-31129	2.6658399	0.0527445	0.0401313	0.0126132
8:97000000-98000000	2.4801782	0.0573864	0.0455562	0.0118302
4:72000000-73000000	2.4445720	0.0585978	0.0479873	0.0106105
7:28000000-29000000	2.7692493	0.0494709	0.0411905	0.0082804
13:10000000-11000000	2.5285473	0.0501536	0.0424944	0.0076592
7:16000000-17000000	2.7012987	0.0424617	0.0371710	0.0052907
12:103000000-104000000	2.6786553	0.0429386	0.0390614	0.0038772
6:69000000-70000000	2.3974372	0.0561423	0.0522785	0.0038638
12:21000000-22000000	2.5931705	0.0424735	0.0387579	0.0037156
1:25000000-26000000	2.4790582	0.0488686	0.0456327	0.0032359
10:10000000-11000000	2.5362313	0.0451568	0.0420142	0.0031426
14:87000000-88000000	2.5542879	0.0433995	0.0409641	0.0024353
5:29000000-30000000	2.6494743	0.0430374	0.0414976	0.0015399
7:128000000-129000000	2.6682400	0.0413924	0.0399309	0.0014615
12:87000000-88000000	2.5838581	0.0404949	0.0392863	0.0012087
19:13000000-14000000	2.4366662	0.0489904	0.0485271	0.0004633
13:65000000-66000000	2.3691627	0.0559565	0.0555834	0.0003730
9:14000000-15000000	2.6974083	0.0378582	0.0374958	0.0003624
2:129000000-130000000	2.6828381	0.0390324	0.0387122	0.0003202
1:171000000-172000000	2.6712769	0.0399403	0.0396774	0.0002629
6:89000000-90000000	2.7063029	0.0374171	0.0373648	0.0000523
5:118000000-119000000	2.7828105	0.0423867	0.0423475	0.0000391
5:36000000-37000000	2.8122551	0.0448508	0.0448427	0.0000081
2:98000000-99000000	4.0988731	0.0607716	0.0607716	0.0000000
12:115000000-116000000	2.5875864	0.0390576	0.0390747	-0.0000171
14:106000000-107000000	2.4730892	0.0460103	0.0460402	-0.0000300
7:32000000-33000000	1.5875071	0.2588853	0.2589236	-0.0000383
Y:63000000-64000000	-0.9195701	1.4904793	1.4905269	-0.0000476
7:31000000-32000000	2.2427005	0.0794817	0.0795310	-0.0000492
6:18000000-19000000	2.5083986	0.0435255	0.0437536	-0.0002281
19:7000000-8000000	2.6751590	0.0389104	0.0393533	-0.0004429
9:46000000-47000000	2.7608327	0.0400178	0.0404724	-0.0004546
2:131000000-132000000	2.7015040	0.0366087	0.0371538	-0.0005452
9:11000000-12000000	2.4240253	0.0490762	0.0496653	-0.0005891
11:23000000-24000000	2.6061537	0.0386018	0.0393283	-0.0007265
17:20000000-21000000	2.4177928	0.0494872	0.0502779	-0.0007907
10:80000000-81000000	2.8392920	0.0461949	0.0469921	-0.0007972
5:111000000-112000000	2.7785040	0.0411075	0.0419801	-0.0008726
5:131000000-132000000	2.6877342	0.0372334	0.0383034	-0.0010700
10:19000000-20000000	2.6166163	0.0388218	0.0398973	-0.0010755
16:57000000-58000000	2.5703680	0.0389255	0.0400517	-0.0011262
2:152000000-153000000	2.7423586	0.0381674	0.0393108	-0.0011434
2:63000000-64000000	2.4474712	0.0466174	0.0477894	-0.0011720
12:16000000-17000000	2.6833722	0.0373490	0.0386676	-0.0013186
19:41000000-42000000	2.7235121	0.0369366	0.0382936	-0.0013570
14:60000000-61000000	2.6857272	0.0369226	0.0384710	-0.0015484
9:37000000-38000000	2.6114010	0.0380065	0.0396137	-0.0016071
9:122000000-123000000	2.7099953	0.0358955	0.0375640	-0.0016686

plot(y$logMean,y$cv,pch=18,cex=0.5,xlab="log10(mean)",ylab="CV")
lines(predict(Rbs.9), col = "red", lwd = 1.0)
lines(predict(Rbs.median), col = "blue", lwd = 1.0)
points(yy$logMean,yy$cv)
text(yy$logMean,yy$cv+0.02,labels=rownames(yy),cex=0.8)

my_palette <- colorRampPalette(c("blue", "white", "red"))(n = 25)
zz <- x[which(rownames(x) %in% rownames(yy)),]
heatmap.2(as.matrix(zz),margin=c(8, 22),cexRow=0.65,trace="none",
  cexCol=0.8,col=my_palette,scale="row")

heatmap.2(cor(t(zz)),trace="none",scale="none",margins=c(12,12),
  cexRow=0.8, cexCol=0.8)

Now fixed up a bit.

x <- read.table("SRP199233.1e6_fmt.tsv",header=T,row.names=1)

x <- x[grep("X",rownames(x),invert=TRUE),]
x <- x[grep("Y",rownames(x),invert=TRUE),]
x <- x[grep("M",rownames(x),invert=TRUE),]
x <- x[grep("J",rownames(x),invert=TRUE),]
x <- x[grep("G",rownames(x),invert=TRUE),]

x <- x[which(rowSums(x)>=10),]
x <- sweep(x, 2, colSums(x), FUN="/")*1000000
mysd <- apply(x,1,sd)
mean <- apply(x,1,mean)
y <- data.frame(log10(mean),mysd/mean)
colnames(y) <- c("logMean","cv")
Rbs.9 <- cobs(y$logMean,y$cv, nknots=10,constraint="none",tau=0.99)

## qbsks2():
##  Performing general knot selection ...
## 
##  WARNING! Since the number of  10  knots selected by  AIC  reached the
##    upper bound during general knot selection, you might want to rerun
##    cobs with a larger number of knots. 
## 
##  Deleting unnecessary knots ...
## 
##  WARNING! Since the number of  10  knots selected by  AIC  reached the
##    upper bound during general knot selection, you might want to rerun
##    cobs with a larger number of knots.

Rbs.median <- cobs(y$logMean,y$cv,nknots=10,constraint="none",tau=0.5)

## qbsks2():
##  Performing general knot selection ...
## 
##  Deleting unnecessary knots ...

pred <- data.frame(predict(Rbs.9))

res <- mclapply(X=1:nrow(y),function(row) {
  interpolate_points(row,y,pred)
  },mc.cores=8)
y$interpolated <- unlist(res)

y$diff <- y$cv-y$interpolated
yy <- y[order(-y$diff),]
yy <- head(yy,50)

write.table(yy,file="SRP199233.1e6_regions.tsv")

yy %>% kbl() %>% kable_paper("hover", full_width = F)

	logMean	cv	interpolated	diff
8:97000000-98000000	2.491946	0.0576254	0.0444597	0.0131656
4:72000000-73000000	2.456341	0.0588557	0.0480012	0.0108545
7:28000000-29000000	2.781010	0.0493569	0.0406575	0.0086994
13:10000000-11000000	2.540312	0.0502447	0.0421066	0.0081381
7:16000000-17000000	2.713062	0.0424653	0.0372215	0.0052438
1:25000000-26000000	2.490826	0.0491547	0.0444808	0.0046739
10:10000000-11000000	2.547997	0.0453420	0.0415737	0.0037683
5:29000000-30000000	2.661236	0.0429821	0.0393844	0.0035977
12:103000000-104000000	2.690415	0.0427163	0.0392618	0.0034545
12:21000000-22000000	2.604930	0.0422757	0.0389109	0.0033648
14:87000000-88000000	2.566054	0.0436054	0.0404302	0.0031751
14:106000000-107000000	2.484854	0.0461552	0.0445930	0.0015622
7:128000000-129000000	2.679999	0.0411291	0.0395942	0.0015349
12:87000000-88000000	2.595620	0.0404222	0.0391221	0.0013001
6:89000000-90000000	2.718062	0.0371048	0.0367711	0.0003337
5:118000000-119000000	2.794570	0.0421634	0.0418907	0.0002727
1:171000000-172000000	2.683038	0.0398373	0.0396282	0.0002091
6:18000000-19000000	2.520165	0.0437202	0.0435219	0.0001982
10:19000000-20000000	2.628382	0.0389898	0.0388623	0.0001275
12:115000000-116000000	2.599351	0.0391572	0.0390374	0.0001198
15:93000000-94000000	2.645251	0.0392038	0.0391652	0.0000386
9:124000000-124359700	2.050790	0.1535983	0.1535894	0.0000089
7:32000000-33000000	1.599280	0.2589433	0.2589344	0.0000088
5:36000000-37000000	2.824012	0.0444906	0.0444888	0.0000019
2:98000000-99000000	4.110644	0.0611200	0.0611200	0.0000000
14:50000000-51000000	2.477492	0.0447314	0.0447316	-0.0000002
9:14000000-15000000	2.709167	0.0375699	0.0375724	-0.0000025
19:13000000-14000000	2.448433	0.0492152	0.0492235	-0.0000083
11:23000000-24000000	2.617917	0.0386465	0.0386744	-0.0000279
2:129000000-130000000	2.694598	0.0388437	0.0388849	-0.0000412
9:46000000-47000000	2.772592	0.0397672	0.0398812	-0.0001140
16:57000000-58000000	2.582134	0.0391847	0.0394280	-0.0002433
2:152000000-153000000	2.754117	0.0378567	0.0382337	-0.0003770
13:30000000-31000000	2.644148	0.0387629	0.0391454	-0.0003825
19:7000000-8000000	2.686924	0.0390917	0.0395762	-0.0004846
9:37000000-38000000	2.623167	0.0382618	0.0387687	-0.0005069
10:80000000-81000000	2.851055	0.0462224	0.0467717	-0.0005494
5:111000000-112000000	2.790265	0.0409462	0.0415107	-0.0005646
2:63000000-64000000	2.459239	0.0469329	0.0475531	-0.0006202
19:41000000-42000000	2.735271	0.0366452	0.0372724	-0.0006272
18:86000000-87000000	2.465841	0.0457070	0.0465327	-0.0008257
2:131000000-132000000	2.713264	0.0363743	0.0372033	-0.0008290
9:122000000-123000000	2.721756	0.0356884	0.0365830	-0.0008946
8:23000000-24000000	2.720346	0.0355879	0.0365653	-0.0009774
7:46000000-47000000	2.728042	0.0358622	0.0369037	-0.0010415
8:3000000-4000000	2.630171	0.0375803	0.0388944	-0.0013141
13:118000000-119000000	2.484165	0.0431665	0.0446059	-0.0014394
19:58000000-59000000	2.739115	0.0359795	0.0374685	-0.0014890
5:131000000-132000000	2.699493	0.0369483	0.0384439	-0.0014956
10:122000000-123000000	2.619504	0.0371110	0.0387029	-0.0015918

plot(y$logMean,y$cv,pch=18,cex=0.5,xlab="log10(mean)",ylab="CV")
lines(predict(Rbs.9), col = "red", lwd = 1.0)
lines(predict(Rbs.median), col = "blue", lwd = 1.0)
points(yy$logMean,yy$cv)

#text(yy$logMean,yy$cv+0.02,labels=rownames(yy),cex=0.8)

plot(y$logMean,y$cv,pch=18,cex=0.5,xlab="log10(mean)",ylab="CV",xlim=c(1,4.5),ylim=c(0,0.3))
#lines(predict(Rbs.9), col = "red", lwd = 1.0)
#lines(predict(Rbs.median), col = "blue", lwd = 1.0)
points(yy$logMean,yy$cv)
text(yy$logMean,yy$cv+0.02,labels=rownames(yy),cex=0.8)

my_palette <- colorRampPalette(c("blue", "white", "red"))(n = 25)
zz <- x[which(rownames(x) %in% rownames(yy)),]
heatmap.2(as.matrix(zz),margin=c(8, 22),cexRow=0.65,trace="none",
  cexCol=0.8,col=my_palette,scale="row")

heatmap.2(cor(t(zz)),trace="none",scale="none",margins=c(12,12),
  cexRow=0.8, cexCol=0.8)

for (i in 1:19){
mychr=as.character(i)
regex=paste("^",mychr,":",sep="")
chr <- x[grep(regex,rownames(x)),]
mymax = max(chr)
plot(chr[,1], xaxt = "n", pch=19, col="gray",
  ylim=c(0,mymax),ylab="RPM of 1Mbp bins of chr",main=mychr)
axis(1, at=chr[,1], labels=rownames(chr), xlab="chr", las=1)
points( chr[,1], xaxt = "n", las=1, pch=19, col="gray"  )
points( chr[,2], xaxt = "n", las=1, pch=19, col="lightblue"  )
points( chr[,3], xaxt = "n", las=1, pch=19, col="lightgreen"  )
points( chr[,4], xaxt = "n", las=1, pch=19, col="pink" )
points( chr[,5], xaxt = "n", las=1, pch=19, col="orange" )
points( chr[,6], xaxt = "n", las=1, pch=19, col="black" )
grid()
}

lapply(1:19,function(i){
  mychr=as.character(i)
  regex=paste("^",mychr,":",sep="")
  chr <- x[grep(regex,rownames(x)),]
  mymedian <- median(rowMeans(chr))
  mymax <- max(rowMeans(chr))
  rat <- mymax / mymedian
  return(c(mymax,mymedian,rat))
})

## [[1]]
## [1] 700.467728 384.117157   1.823578
## 
## [[2]]
## [1] 12901.60683   413.41352    31.20751
## 
## [[3]]
## [1] 576.258958 369.878762   1.557967
## 
## [[4]]
## [1] 716.842941 385.712263   1.858491
## 
## [[5]]
## [1] 736.167517 429.930486   1.712294
## 
## [[6]]
## [1] 1066.954018  387.482317    2.753555
## 
## [[7]]
## [1] 666.247660 447.651643   1.488317
## 
## [[8]]
## [1] 701.537192 418.892094   1.674744
## 
## [[9]]
## [1] 968.765313 460.571348   2.103399
## 
## [[10]]
## [1] 709.66815 391.16988   1.81422
## 
## [[11]]
## [1] 782.248865 487.291608   1.605299
## 
## [[12]]
## [1] 707.150783 397.787995   1.777708
## 
## [[13]]
## [1] 599.085444 394.550092   1.518401
## 
## [[14]]
## [1] 710.758402 369.484692   1.923648
## 
## [[15]]
## [1] 693.714336 388.136775   1.787294
## 
## [[16]]
## [1] 622.386018 374.072480   1.663811
## 
## [[17]]
## [1] 692.022110 430.531079   1.607369
## 
## [[18]]
## [1] 603.882543 394.316248   1.531468
## 
## [[19]]
## [1] 637.478821 444.900515   1.432857

lapply(1:19,function(i){
  mychr=as.character(i)
  regex=paste("^",mychr,":",sep="")
  chr <- x[grep(regex,rownames(x)),]
  top <- head(chr[order(-rowMeans(chr)),])
  return(top)
})

## [[1]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 1:88000000-89000000         702.1750       680.7719       717.2025
## 1:92000000-93000000         613.2773       586.3729       621.3214
## 1:135000000-136000000       615.3736       604.0265       613.5023
## 1:91000000-92000000         608.2308       624.1114       610.7657
## 1:132000000-133000000       614.2867       590.7070       628.7495
## 1:133000000-134000000       586.5692       566.4995       600.4054
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 1:88000000-89000000         709.7236       701.4596       691.4738
## 1:92000000-93000000         626.6750       637.8441       620.7884
## 1:135000000-136000000       615.7014       644.5243       601.6941
## 1:91000000-92000000         613.1871       628.2461       598.1013
## 1:132000000-133000000       609.0753       607.9367       602.7033
## 1:133000000-134000000       587.3638       604.2511       587.6862
## 
## [[2]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 2:98000000-99000000       13985.8136     13197.7780     11944.7740
## 2:27000000-28000000         717.6253       714.4934       755.6136
## 2:31000000-32000000         671.8178       680.3491       704.3988
## 2:179000000-180000000       642.1594       685.3174       718.6686
## 2:25000000-26000000         671.0414       679.6091       673.2203
## 2:167000000-168000000       659.2402       681.5119       690.8132
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 2:98000000-99000000       13129.7418     11998.7555     13152.7780
## 2:27000000-28000000         730.7018       759.9689       723.3247
## 2:31000000-32000000         670.0457       695.2785       680.1303
## 2:179000000-180000000       673.0313       681.1118       656.3128
## 2:25000000-26000000         675.0218       697.3132       656.3128
## 2:167000000-168000000       662.2410       683.9144       669.4730
## 
## [[3]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 3:89000000-90000000         571.5071       559.0998       586.4289
## 3:107000000-108000000       559.2400       549.9030       568.9337
## 3:101000000-102000000       542.3921       535.7379       546.0630
## 3:88000000-89000000         506.2120       539.2263       502.2763
## 3:153000000-154000000       502.9511       534.1522       518.9895
## 3:87000000-88000000         500.6219       525.6954       513.3207
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 3:89000000-90000000         590.2185       578.7205       571.5791
## 3:107000000-108000000       558.7119       560.8298       551.4755
## 3:101000000-102000000       544.3335       549.6577       525.0745
## 3:88000000-89000000         512.6174       516.0264       514.1749
## 3:153000000-154000000       513.0103       511.3426       487.7739
## 3:87000000-88000000         503.4247       511.1506       511.9547
## 
## [[4]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 4:154000000-155000000       700.7775       702.1253       725.2170
## 4:140000000-141000000       695.2651       696.2055       713.1952
## 4:152000000-153000000       686.6470       699.0597       732.3519
## 4:139000000-140000000       670.2650       697.0512       682.9941
## 4:125000000-126000000       657.5321       636.9023       671.4610
## 4:138000000-139000000       640.8395       650.0103       668.7244
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 4:154000000-155000000       718.4972       751.1388       703.3018
## 4:140000000-141000000       696.7857       720.8091       676.1741
## 4:152000000-153000000       677.9551       684.5671       683.7634
## 4:139000000-140000000       698.3571       707.5255       677.4659
## 4:125000000-126000000       668.1076       684.0680       667.0508
## 4:138000000-139000000       655.5888       675.2379       643.1930
## 
## [[5]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 5:35000000-36000000         731.1347       707.1994       760.3050
## 5:139000000-140000000       694.6439       698.8483       717.3980
## 5:140000000-141000000       681.6781       659.8413       676.1525
## 5:36000000-37000000         636.3364       644.0906       707.8196
## 5:113000000-114000000       651.8644       640.3907       689.9336
## 5:112000000-113000000       659.7836       658.5728       679.4756
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 5:35000000-36000000         733.4255       761.6966       723.2439
## 5:139000000-140000000       695.5809       707.1800       678.8385
## 5:140000000-141000000       690.7096       721.6537       690.5050
## 5:36000000-37000000         668.8933       696.5838       647.2299
## 5:113000000-114000000       641.5771       651.4732       627.6915
## 5:112000000-113000000       625.4964       651.3581       619.7792
## 
## [[6]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 6:103000000-104000000      1103.0297      1084.9009      1074.7286
## 6:91000000-92000000         646.8954       649.7989       668.1380
## 6:88000000-89000000         609.8612       625.6970       618.2915
## 6:113000000-114000000       579.8146       589.0157       619.4644
## 6:127000000-128000000       578.8829       575.6962       580.1736
## 6:90000000-91000000         587.1904       560.6854       570.3998
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 6:103000000-104000000      1048.5439      1035.1241      1055.3968
## 6:91000000-92000000         660.8530       691.7464       646.9473
## 6:88000000-89000000         622.3012       632.8531       598.1820
## 6:113000000-114000000       592.3399       601.1798       585.9099
## 6:127000000-128000000       602.6849       611.2768       570.6506
## 6:90000000-91000000         580.7639       594.6531       567.1385
## 
## [[7]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 7:141000000-142000000       658.2308       653.3930       687.3924
## 7:143000000-144000000       657.1439       645.1477       643.8989
## 7:125000000-126000000       642.0817       625.5913       657.0935
## 7:144000000-144995196       618.5569       620.7287       629.8246
## 7:45000000-46000000         638.2774       659.5242       633.5386
## 7:44000000-45000000         647.9824       660.3699       647.6129
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 7:141000000-142000000       667.0338       682.9546       648.4813
## 7:143000000-144000000       671.9837       683.6457       642.1838
## 7:125000000-126000000       655.8769       657.4240       634.7560
## 7:144000000-144995196       629.8702       677.0807       629.9925
## 7:45000000-46000000         628.3773       640.9538       603.9951
## 7:44000000-45000000         619.2894       626.9024       602.5014
## 
## [[8]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 8:122000000-123000000       696.7402       685.8460       721.9917
## 8:121000000-122000000       694.5663       686.5859       727.0741
## 8:123000000-124000000       680.5911       665.1268       724.9238
## 8:120000000-121000000       667.3147       639.3336       687.8811
## 8:12000000-13000000         647.9824       617.8745       621.6146
## 8:125000000-126000000       616.4606       608.3606       625.1332
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 8:122000000-123000000       699.9023       725.3394       679.4036
## 8:121000000-122000000       683.9788       708.1014       675.0035
## 8:123000000-124000000       702.3904       707.0264       681.1799
## 8:120000000-121000000       675.8337       685.9876       669.7959
## 8:12000000-13000000         604.4920       643.8716       614.5313
## 8:125000000-126000000       618.4251       645.0618       609.0008
## 
## [[9]]
##                     SRX5884275.bam SRX5884276.bam SRX5884277.bam SRX5884278.bam
## 9:3000000-4000000        1011.2593       986.8021       906.7168       976.1809
## 9:35000000-36000000       707.2216       684.0489       677.6186       697.1262
## 9:45000000-46000000       630.1252       630.1368       626.5015       643.6723
## 9:61000000-62000000       595.1096       619.1430       626.5992       640.4771
## 9:43000000-44000000       602.8736       629.6083       627.5766       630.8130
## 9:21000000-22000000       619.3333       610.5805       630.0201       599.9088
##                     SRX5884279.bam SRX5884280.bam
## 9:3000000-4000000         930.0069      1001.6258
## 9:35000000-36000000       675.8521       691.1913
## 9:45000000-46000000       658.9597       634.1101
## 9:61000000-62000000       656.3874       651.0649
## 9:43000000-44000000       654.0839       624.0179
## 9:21000000-22000000       616.3446       588.4532
## 
## [[10]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 10:80000000-81000000       730.2806       737.2210       741.0506
## 10:60000000-61000000       647.0507       669.7781       674.4909
## 10:77000000-78000000       614.2867       617.7688       640.1848
## 10:61000000-62000000       616.8488       594.6183       638.6210
## 10:76000000-77000000       591.3829       595.1469       604.6082
## 10:79000000-80000000       577.2524       575.5905       575.0912
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 10:80000000-81000000       669.2076       710.2513       669.9977
## 10:60000000-61000000       673.2932       685.2965       670.4014
## 10:77000000-78000000       620.1537       645.1769       604.1566
## 10:61000000-62000000       622.6679       634.2736       609.6063
## 10:76000000-77000000       607.0587       623.2935       583.6897
## 10:79000000-80000000       550.5668       565.0145       534.6418
## 
## [[11]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 11:3000000-4000000           773.6813       784.6847       805.6555
## 11:119000000-120000000       708.3862       727.2843       736.7501
## 11:118000000-119000000       694.8769       693.5628       735.9682
## 11:117000000-118000000       665.9948       687.5373       691.3019
## 11:120000000-121000000       628.1842       669.0381       683.0919
## 11:115000000-116000000       639.1314       643.7734       638.8165
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 11:3000000-4000000           779.3367       781.3148       768.8201
## 11:119000000-120000000       715.0139       729.0634       700.4760
## 11:118000000-119000000       712.1330       734.0927       704.9166
## 11:117000000-118000000       677.2217       705.3755       673.5906
## 11:120000000-121000000       628.3511       667.0220       632.7779
## 11:115000000-116000000       636.3653       644.1788       622.9280
## 
## [[12]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 12:112000000-113000000       693.4793       692.0829       723.2623
## 12:108000000-109000000       593.3239       612.0604       620.4417
## 12:110000000-111000000       579.8922       604.5550       616.5322
## 12:111000000-112000000       593.1686       610.7919       620.0508
## 12:86000000-87000000         593.4015       582.7788       587.3085
## 12:105000000-106000000       586.4916       575.5905       580.8578
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 12:112000000-113000000       706.3189       738.5078       689.2536
## 12:108000000-109000000       617.8489       638.2664       604.8428
## 12:110000000-111000000       609.6777       628.2077       601.2904
## 12:111000000-112000000       601.4278       616.1142       586.5558
## 12:86000000-87000000         590.7161       611.7375       582.0346
## 12:105000000-106000000       586.9971       595.4977       583.7300
## 
## [[13]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 13:48000000-49000000       594.8767       622.9486       604.7059
## 13:56000000-57000000       583.4636       593.3498       601.4805
## 13:73000000-74000000       573.0599       602.0180       562.0921
## 13:52000000-53000000       552.5630       575.1677       566.7835
## 13:55000000-56000000       553.8828       569.8822       580.3691
## 13:49000000-50000000       543.4791       558.2541       540.9806
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 13:48000000-49000000       586.6042       602.2931       583.0841
## 13:56000000-57000000       583.8019       589.5470       573.0727
## 13:73000000-74000000       574.6354       579.7186       576.7463
## 13:52000000-53000000       569.9212       561.5976       557.1675
## 13:55000000-56000000       555.2024       546.1641       546.8735
## 13:49000000-50000000       539.9074       555.8388       536.8621
## 
## [[14]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 14:25000000-26000000       707.4545       684.3660       725.8035
## 14:70000000-71000000       555.5909       603.0751       579.6849
## 14:64000000-65000000       555.8238       571.6793       560.6260
## 14:32000000-33000000       545.8083       559.5226       578.1211
## 14:55000000-56000000       557.6096       546.9431       556.1300
## 14:24000000-25000000       535.5598       549.4802       560.5283
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 14:25000000-26000000       703.7260       731.0982       712.1022
## 14:70000000-71000000       566.3332       583.0204       564.2320
## 14:64000000-65000000       565.8094       583.6730       568.6725
## 14:32000000-33000000       556.5119       570.9653       532.5023
## 14:55000000-56000000       549.0477       557.7968       547.8020
## 14:24000000-25000000       541.8455       558.9870       565.4431
## 
## [[15]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 15:78000000-79000000       699.3800       673.0551       713.1952
## 15:83000000-84000000       647.7495       651.2788       663.1533
## 15:84000000-85000000       634.1625       665.7611       657.8754
## 15:74000000-75000000       635.0165       632.9910       656.7026
## 15:79000000-80000000       646.6625       617.9802       645.9514
## 15:85000000-86000000       630.3581       633.8367       648.2971
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 15:78000000-79000000       684.6073       700.6149       691.4335
## 15:83000000-84000000       660.1458       680.0752       652.3163
## 15:84000000-85000000       662.1625       672.0513       647.2702
## 15:74000000-75000000       653.3626       664.2194       642.2241
## 15:79000000-80000000       647.1556       655.3508       610.0907
## 15:85000000-86000000       628.8488       648.5938       632.6164
## 
## [[16]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 16:10000000-11000000       609.2401       618.9316       622.8852
## 16:17000000-18000000       570.4201       593.2441       607.1493
## 16:4000000-5000000         571.4295       570.3050       571.0840
## 16:92000000-93000000       564.6748       562.3768       578.6098
## 16:95000000-96000000       552.0195       566.7109       541.2738
## 16:18000000-19000000       558.9294       552.9686       568.1518
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 16:10000000-11000000       619.8918       637.6137       625.7538
## 16:17000000-18000000       590.0875       604.9422       585.1026
## 16:4000000-5000000         560.8856       579.8722       566.2101
## 16:92000000-93000000       574.8711       567.3564       559.2667
## 16:95000000-96000000       549.8073       550.1184       560.3162
## 16:18000000-19000000       543.0240       544.4748       546.8331
## 
## [[17]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 17:25000000-26000000       667.2371       688.2773       726.9763
## 17:27000000-28000000       682.0663       671.7866       691.2042
## 17:31000000-32000000       623.6811       637.0080       628.8472
## 17:26000000-27000000       621.0413       636.0566       629.8246
## 17:28000000-29000000       616.3829       637.4308       630.8020
## 17:46000000-47000000       618.0134       608.0435       634.5160
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 17:25000000-26000000       697.1523       704.1470       668.3426
## 17:27000000-28000000       655.4316       666.9068       644.3637
## 17:31000000-32000000       643.5152       645.1002       641.9416
## 17:26000000-27000000       633.0392       651.1661       614.7735
## 17:28000000-29000000       621.3846       642.7583       606.6594
## 17:46000000-47000000       626.7797       628.0541       609.8082
## 
## [[18]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 18:61000000-62000000       595.4978       603.1808       605.0968
## 18:75000000-76000000       584.9388       587.2186       589.7520
## 18:38000000-39000000       543.6344       552.4400       560.7237
## 18:80000000-81000000       563.7431       539.9663       540.7852
## 18:12000000-13000000       520.2648       551.0658       555.0549
## 18:76000000-77000000       519.7213       520.6214       531.2068
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 18:61000000-62000000       607.6086       613.0429       598.8683
## 18:75000000-76000000       583.6710       602.1012       566.2101
## 18:38000000-39000000       553.8929       547.0471       552.3233
## 18:80000000-81000000       545.7740       556.2995       534.7226
## 18:12000000-13000000       542.7883       545.5498       534.1170
## 18:76000000-77000000       524.9267       525.5476       509.5325
## 
## [[19]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 19:10000000-11000000       614.4419       634.7881       641.8464
## 19:6000000-7000000         624.3022       640.8135       616.7277
## 19:5000000-6000000         615.1407       637.6422       632.9522
## 19:4000000-5000000         589.9854       605.0836       580.6623
## 19:56000000-57000000       562.5785       561.4254       588.8723
## 19:47000000-48000000       562.8114       566.1823       574.0161
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 19:10000000-11000000       634.1653       658.5373       641.0938
## 19:6000000-7000000         619.7870       631.7781       582.5997
## 19:5000000-6000000         602.1611       618.6865       587.7669
## 19:4000000-5000000         603.3659       610.4706       591.6423
## 19:56000000-57000000       575.3425       579.9106       568.1881
## 19:47000000-48000000       556.7738       562.4807       558.8630

100 kbp bins

x<-read.table("SRP199233.1e5_fmt.tsv",header=T,row.names=1)

x <- x[grep("X",rownames(x),invert=TRUE),]
x <- x[grep("Y",rownames(x),invert=TRUE),]
x <- x[grep("M",rownames(x),invert=TRUE),]
x <- x[grep("J",rownames(x),invert=TRUE),]
x <- x[grep("G",rownames(x),invert=TRUE),]

x <- x[which(rowSums(x)>=10),]
x <- sweep(x, 2, colSums(x), FUN="/")*1000000
mysd <- apply(x,1,sd)
mean <- apply(x,1,mean)
y <- data.frame(log10(mean),mysd/mean)
colnames(y) <- c("logMean","cv")
Rbs.9 <- cobs(y$logMean,y$cv, nknots=10,constraint="none",tau=0.99)

## qbsks2():
##  Performing general knot selection ...
## 
##  WARNING! Since the number of  10  knots selected by  AIC  reached the
##    upper bound during general knot selection, you might want to rerun
##    cobs with a larger number of knots. 
## 
##  Deleting unnecessary knots ...
## 
##  WARNING! Since the number of  10  knots selected by  AIC  reached the
##    upper bound during general knot selection, you might want to rerun
##    cobs with a larger number of knots.

Rbs.median <- cobs(y$logMean,y$cv,nknots=10,constraint="none",tau=0.5)

## qbsks2():
##  Performing general knot selection ...
## 
##  Deleting unnecessary knots ...

pred <- data.frame(predict(Rbs.9))

res <- mclapply(X=1:nrow(y),function(row) {
  interpolate_points(row,y,pred)
  },mc.cores=8)
y$interpolated <- unlist(res)

y$diff <- y$cv-y$interpolated
yy1 <- y[order(-y$diff),]
yy1 <- head(yy,50)
yy2 <- subset(y,logMean>2 & cv>0.05)
yy <- rbind(yy1,yy2)

write.table(yy,file="SRP199233.1e5_regions.tsv")

yy %>% kbl() %>% kable_paper("hover", full_width = F)

	logMean	cv	interpolated	diff
8:97000000-98000000	2.491946	0.0576254	0.0444597	0.0131656
4:72000000-73000000	2.456341	0.0588557	0.0480012	0.0108545
7:28000000-29000000	2.781010	0.0493569	0.0406575	0.0086994
13:10000000-11000000	2.540312	0.0502447	0.0421066	0.0081381
7:16000000-17000000	2.713062	0.0424653	0.0372215	0.0052438
1:25000000-26000000	2.490826	0.0491547	0.0444808	0.0046739
10:10000000-11000000	2.547997	0.0453420	0.0415737	0.0037683
5:29000000-30000000	2.661236	0.0429821	0.0393844	0.0035977
12:103000000-104000000	2.690415	0.0427163	0.0392618	0.0034545
12:21000000-22000000	2.604930	0.0422757	0.0389109	0.0033648
14:87000000-88000000	2.566054	0.0436054	0.0404302	0.0031751
14:106000000-107000000	2.484854	0.0461552	0.0445930	0.0015622
7:128000000-129000000	2.679999	0.0411291	0.0395942	0.0015349
12:87000000-88000000	2.595620	0.0404222	0.0391221	0.0013001
6:89000000-90000000	2.718062	0.0371048	0.0367711	0.0003337
5:118000000-119000000	2.794570	0.0421634	0.0418907	0.0002727
1:171000000-172000000	2.683038	0.0398373	0.0396282	0.0002091
6:18000000-19000000	2.520165	0.0437202	0.0435219	0.0001982
10:19000000-20000000	2.628382	0.0389898	0.0388623	0.0001275
12:115000000-116000000	2.599351	0.0391572	0.0390374	0.0001198
15:93000000-94000000	2.645251	0.0392038	0.0391652	0.0000386
9:124000000-124359700	2.050790	0.1535983	0.1535894	0.0000089
7:32000000-33000000	1.599280	0.2589433	0.2589344	0.0000088
5:36000000-37000000	2.824012	0.0444906	0.0444888	0.0000019
2:98000000-99000000	4.110644	0.0611200	0.0611200	0.0000000
14:50000000-51000000	2.477492	0.0447314	0.0447316	-0.0000002
9:14000000-15000000	2.709167	0.0375699	0.0375724	-0.0000025
19:13000000-14000000	2.448433	0.0492152	0.0492235	-0.0000083
11:23000000-24000000	2.617917	0.0386465	0.0386744	-0.0000279
2:129000000-130000000	2.694598	0.0388437	0.0388849	-0.0000412
9:46000000-47000000	2.772592	0.0397672	0.0398812	-0.0001140
16:57000000-58000000	2.582134	0.0391847	0.0394280	-0.0002433
2:152000000-153000000	2.754117	0.0378567	0.0382337	-0.0003770
13:30000000-31000000	2.644148	0.0387629	0.0391454	-0.0003825
19:7000000-8000000	2.686924	0.0390917	0.0395762	-0.0004846
9:37000000-38000000	2.623167	0.0382618	0.0387687	-0.0005069
10:80000000-81000000	2.851055	0.0462224	0.0467717	-0.0005494
5:111000000-112000000	2.790265	0.0409462	0.0415107	-0.0005646
2:63000000-64000000	2.459239	0.0469329	0.0475531	-0.0006202
19:41000000-42000000	2.735271	0.0366452	0.0372724	-0.0006272
18:86000000-87000000	2.465841	0.0457070	0.0465327	-0.0008257
2:131000000-132000000	2.713264	0.0363743	0.0372033	-0.0008290
9:122000000-123000000	2.721756	0.0356884	0.0365830	-0.0008946
8:23000000-24000000	2.720346	0.0355879	0.0365653	-0.0009774
7:46000000-47000000	2.728042	0.0358622	0.0369037	-0.0010415
8:3000000-4000000	2.630171	0.0375803	0.0388944	-0.0013141
13:118000000-119000000	2.484165	0.0431665	0.0446059	-0.0014394
19:58000000-59000000	2.739115	0.0359795	0.0374685	-0.0014890
5:131000000-132000000	2.699493	0.0369483	0.0384439	-0.0014956
10:122000000-123000000	2.619504	0.0371110	0.0387029	-0.0015918
2:98400000-98500000	4.103646	0.0616973	0.0616973	0.0000000
3:3000000-3100000	2.100321	0.0503498	0.1079735	-0.0576237
4:3000000-3100000	2.065077	0.1047348	0.1072179	-0.0024831
9:3000000-3100000	2.839527	0.0506325	0.1113817	-0.0607492
12:3100000-3200000	2.142286	0.0897696	0.1088047	-0.0190351
12:115500000-115600000	2.004164	0.0681790	0.1057779	-0.0375989
13:48400000-48500000	2.153410	0.0638206	0.1090170	-0.0451963
14:3000000-3100000	2.188414	0.0652794	0.1096344	-0.0443551
17:13700000-13800000	2.070077	0.0764565	0.1073251	-0.0308685
17:40100000-40200000	2.319788	0.0922489	0.1114911	-0.0192422

plot(y$logMean,y$cv,pch=18,cex=0.5,xlab="log10(mean)",ylab="CV")
lines(predict(Rbs.9), col = "red", lwd = 1.0)
lines(predict(Rbs.median), col = "blue", lwd = 1.0)
points(yy$logMean,yy$cv)

#text(yy$logMean,yy$cv+0.02,labels=rownames(yy),cex=0.8)

plot(y$logMean,y$cv,pch=18,cex=0.5,xlab="log10(mean)",ylab="CV",xlim=c(1,4.5),ylim=c(0,0.35))
lines(predict(Rbs.9), col = "red", lwd = 1.0)
lines(predict(Rbs.median), col = "blue", lwd = 1.0)
points(yy$logMean,yy$cv)
text(yy$logMean,yy$cv+0.02,labels=rownames(yy),cex=0.8)

my_palette <- colorRampPalette(c("blue", "white", "red"))(n = 25)
zz <- x[which(rownames(x) %in% rownames(yy)),]
heatmap.2(as.matrix(zz),margin=c(8, 22),cexRow=0.65,trace="none",
  cexCol=0.8,col=my_palette,scale="row")

heatmap.2(cor(t(zz)),trace="none",scale="none",margins=c(12,12),
  cexRow=0.8, cexCol=0.8)

for (i in 1:19){
mychr=as.character(i)
regex=paste("^",mychr,":",sep="")
chr <- x[grep(regex,rownames(x)),]
mymax = max(chr)
plot(chr[,1], xaxt = "n", pch=19, col="gray",
  ylim=c(0,mymax),ylab="RPM of 100 kbp bins of chr",main=mychr)
axis(1, at=chr[,1], labels=rownames(chr), xlab="chr", las=1)
points( chr[,1], xaxt = "n", las=1, pch=19, col="gray"  )
points( chr[,2], xaxt = "n", las=1, pch=19, col="lightblue"  )
points( chr[,3], xaxt = "n", las=1, pch=19, col="lightgreen"  )
points( chr[,4], xaxt = "n", las=1, pch=19, col="pink" )
points( chr[,5], xaxt = "n", las=1, pch=19, col="orange" )
points( chr[,6], xaxt = "n", las=1, pch=19, col="black" )
grid()
}

lapply(1:19,function(i){
  mychr=as.character(i)
  regex=paste("^",mychr,":",sep="")
  chr <- x[grep(regex,rownames(x)),]
  mymedian <- median(rowMeans(chr))
  mymax <- max(rowMeans(chr))
  rat <- mymax / mymedian
  return(c(mymax,mymedian,rat))
})

## [[1]]
## [1] 189.354189  37.554372   5.042134
## 
## [[2]]
## [1] 12695.38925    41.01708   309.51467
## 
## [[3]]
## [1] 125.985681  35.260139   3.573034
## 
## [[4]]
## [1] 116.165398  39.019478   2.977113
## 
## [[5]]
## [1] 85.242743 42.380372  2.011373
## 
## [[6]]
## [1] 788.10324  38.09023  20.69043
## 
## [[7]]
## [1] 77.314277 43.897365  1.761251
## 
## [[8]]
## [1] 81.805656 40.952229  1.997587
## 
## [[9]]
## [1] 691.07779  45.04618  15.34154
## 
## [[10]]
## [1] 75.544299 38.366680  1.969008
## 
## [[11]]
## [1] 286.042322  48.370843   5.913528
## 
## [[12]]
## [1] 138.766911  38.905723   3.566748
## 
## [[13]]
## [1] 142.367188  39.901643   3.567953
## 
## [[14]]
## [1] 154.31716  36.96556   4.17462
## 
## [[15]]
## [1] 80.80260 39.38287  2.05172
## 
## [[16]]
## [1] 84.968323 36.650925  2.318313
## 
## [[17]]
## [1] 208.827507  42.808724   4.878153
## 
## [[18]]
## [1] 72.580938 39.104282  1.856087
## 
## [[19]]
## [1] 74.559400 43.902405  1.698299

lapply(1:19,function(i){
  mychr=as.character(i)
  regex=paste("^",mychr,":",sep="")
  chr <- x[grep(regex,rownames(x)),]
  top <- head(chr[order(-rowMeans(chr)),])
  return(top)
})

## [[1]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 1:88100000-88200000        195.74939      187.90813      193.69850
## 1:88200000-88300000        115.70895      103.68805      109.86031
## 1:93100000-93200000         74.52309       72.47583       71.51192
## 1:91200000-91300000         73.27974       74.16869       67.69665
## 1:92900000-93000000         71.57014       68.45527       72.58802
## 1:136000000-136100000       71.57014       75.96736       71.51192
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 1:88100000-88200000        184.53991      193.05410      181.17510
## 1:88200000-88300000        115.12774      108.09339      110.66873
## 1:93100000-93200000         71.84999       70.58925       72.68823
## 1:91200000-91300000         72.29561       72.89483       69.81949
## 1:92900000-93000000         73.39656       72.08788       70.10232
## 1:136000000-136100000       69.15004       71.39620       68.16289
## 
## [[2]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 2:98400000-98500000      13774.49344    12996.87338    11747.91177
## 2:27600000-27700000         76.69895       75.86156       92.15353
## 2:31300000-31400000         80.42899       79.77631       74.44675
## 2:166400000-166500000       73.66829       72.89904       81.78381
## 2:25300000-25400000         80.19586       78.71827       76.59895
## 2:26400000-26500000         75.76644       75.86156       77.87071
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 2:98400000-98500000      12917.32200    11797.47318    12938.26172
## 2:27600000-27700000         83.12160       81.11808       79.75906
## 2:31300000-31400000         78.84887       81.46391       76.52668
## 2:166400000-166500000       82.54491       79.81158       77.45599
## 2:25300000-25400000         77.38094       79.85000       75.19332
## 2:26400000-26500000         79.79254       80.31112       77.33478
## 
## [[3]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 3:3000000-3100000          127.13219      124.31985      133.24109
## 3:87600000-87700000         62.78901       68.03205       71.60975
## 3:93700000-93800000         58.67042       62.10702       66.13141
## 3:89200000-89300000         63.72152       65.17534       63.29441
## 3:89400000-89500000         65.27570       59.56772       56.54431
## 3:108300000-108400000       60.45773       64.75213       62.90310
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 3:3000000-3100000          118.14224      132.95525      120.12345
## 3:87600000-87700000         63.59287       66.32392       66.58710
## 3:93700000-93800000         67.13164       68.12996       68.80937
## 3:89200000-89300000         64.51033       68.32209       65.53658
## 3:89400000-89500000         68.78306       62.78869       66.82953
## 3:108300000-108400000       61.52204       67.39986       60.40517
## 
## [[4]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 4:3000000-3100000          122.23652      115.32650      134.80633
## 4:146500000-146600000      105.99530      103.89965      107.51245
## 4:147600000-147700000       92.78474       85.27813       87.06650
## 4:154100000-154200000       77.55375       86.54778       85.01212
## 4:154300000-154400000       86.56801       75.01513       77.38157
## 4:140700000-140800000       79.65189       85.06652       84.62081
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 4:3000000-3100000          105.14057      118.43008      101.05239
## 4:146500000-146600000      104.74737       99.94700      102.87061
## 4:147600000-147700000       83.04296       85.72924       86.46626
## 4:154100000-154200000       78.87508       82.53985       80.48635
## 4:154300000-154400000       80.21195       87.07416       79.31461
## 4:140700000-140800000       75.75573       80.73381       76.60749
## 
## [[5]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 5:125100000-125200000       87.42281       83.90267       81.39250
## 5:140000000-140100000       77.78687       79.24729       75.52285
## 5:35800000-35900000         81.75004       72.47583       79.63161
## 5:36200000-36300000         70.48221       83.58526       77.08809
## 5:35900000-36000000         73.97912       73.85128       88.24043
## 5:139700000-139800000       78.95251       76.49639       79.04464
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 5:125100000-125200000       85.66427       87.49685       85.57736
## 5:140000000-140100000       81.28669       89.03391       82.95104
## 5:35800000-35900000         79.42556       89.14919       77.45599
## 5:36200000-36300000         76.17514       87.30472       74.30442
## 5:35900000-36000000         77.66928       79.23518       75.88020
## 5:139700000-139800000       78.53431       76.89117       76.93073
## 
## [[6]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 6:103600000-103700000      822.16296      808.55515      797.88129
## 6:89300000-89400000         74.67851       76.39058       83.93602
## 6:88200000-88300000         78.79709       70.88877       75.71850
## 6:115900000-116000000       75.14476       78.08345       80.80554
## 6:113800000-113900000       77.00978       66.76241       82.37078
## 6:127900000-128000000       74.05683       80.62275       72.78368
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 6:103600000-103700000      771.47644      753.57962      774.96396
## 6:89300000-89400000         70.72282       80.04214       72.56701
## 6:88200000-88300000         75.96544       81.65604       73.77915
## 6:115900000-116000000       71.53543       75.73838       74.06199
## 6:113800000-113900000       73.39656       77.27544       77.86004
## 6:127900000-128000000       75.99165       76.85275       70.91041
## 
## [[7]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 7:144300000-144400000       73.59058       70.04233       75.42502
## 7:141300000-141400000       76.46582       71.41779       81.49033
## 7:144700000-144800000       68.07323       73.53387       76.50112
## 7:97700000-97800000         69.70512       75.75576       81.88164
## 7:144600000-144700000       67.99552       75.75576       81.29467
## 7:142600000-142700000       76.38811       73.53387       78.16419
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 7:144300000-144400000       77.66928       87.03574       80.12271
## 7:141300000-141400000       76.59455       81.34863       72.93065
## 7:144700000-144800000       74.52372       82.38615       73.65794
## 7:97700000-97800000         71.98105       79.85000       68.52653
## 7:144600000-144700000       72.26939       78.31295       71.92053
## 7:142600000-142700000       74.31401       73.24067       71.51649
## 
## [[8]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 8:122900000-123000000       79.34106       74.16869       85.89257
## 8:121000000-121100000       75.68873       76.28478       93.32746
## 8:123000000-123100000       75.61102       75.43834       99.19711
## 8:123500000-123600000       79.18564       72.89904       75.71850
## 8:122800000-122900000       76.46582       76.39058       72.19671
## 8:123400000-123500000       75.37789       74.80352       77.47940
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 8:122900000-123000000       83.01675       92.45386       75.96101
## 8:121000000-121100000       79.68769       84.69173       79.11259
## 8:123000000-123100000       81.26047       79.15833       77.57721
## 8:123500000-123600000       81.02456       78.27452       76.44587
## 8:122800000-122900000       78.27218       81.80975       72.80944
## 8:123400000-123500000       76.25378       80.77224       72.40539
## 
## [[9]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 9:3000000-3100000          729.14509      702.32781      637.44415
## 9:35200000-35300000        348.99186      338.99643      313.92853
## 9:56600000-56700000         74.21225       70.57135       77.18592
## 9:119300000-119400000       77.78687       75.22674       81.88164
## 9:107300000-107400000       74.52309       72.15842       72.39237
## 9:56500000-56600000         69.54970       78.18925       77.18592
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 9:3000000-3100000          698.47308      661.16419      717.91239
## 9:35200000-35300000        338.69889      319.70743      333.13753
## 9:56600000-56700000         76.90911       81.65604       76.52668
## 9:119300000-119400000       74.65478       76.23793       66.06184
## 9:107300000-107400000       74.31401       78.88935       73.90037
## 9:56500000-56600000         73.63247       77.23701       70.34475
## 
## [[10]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 10:79900000-80000000       76.93207       78.92988       85.50126
## 10:60200000-60300000       74.75622       77.34282       74.54457
## 10:80100000-80200000       71.95869       81.89240       79.43595
## 10:80500000-80600000       73.04662       73.95709       85.10995
## 10:80700000-80800000       69.54970       78.92988       78.65333
## 10:80600000-80700000       79.10793       76.07317       69.65320
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 10:79900000-80000000       69.43838       76.96803       65.49617
## 10:60200000-60300000       75.54603       78.19767       72.68823
## 10:80100000-80200000       67.18406       77.85183       70.50637
## 10:80500000-80600000       68.12773       72.31844       71.07203
## 10:80700000-80800000       65.21808       76.04579       74.02158
## 10:80600000-80700000       69.85779       72.31844       65.65779
## 
## [[11]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 11:3100000-3200000          292.26417      296.78058      293.87388
## 11:119800000-119900000       77.32062       85.59554       83.34905
## 11:118400000-118500000       81.75004       80.62275       81.00119
## 11:119900000-120000000       78.02000       81.68079       86.67519
## 11:58900000-59000000         77.55375       73.21646       85.79474
## 11:115700000-115800000       81.28379       77.13121       78.06636
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 11:3100000-3200000          275.83998      280.35882      277.13649
## 11:119800000-119900000       76.69940       83.00097       77.21356
## 11:118400000-118500000       74.52372       83.76950       80.04190
## 11:119900000-120000000       80.15952       77.92869       75.27413
## 11:58900000-59000000         79.34692       80.69539       82.38538
## 11:115700000-115800000       77.01396       79.19676       76.16304
## 
## [[12]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 12:3100000-3200000          159.45921      148.12578      133.73023
## 12:115500000-115600000      100.78879      101.78357       87.55563
## 12:112100000-112200000       84.08132       81.99820       85.01212
## 12:113600000-113700000       71.10389       76.91960       79.43595
## 12:112400000-112500000       74.05683       73.74548       76.20764
## 12:112200000-112300000       79.03022       69.51331       81.58816
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 12:3100000-3200000          132.16623      126.26906      132.85096
## 12:115500000-115600000      106.39879      104.44288      104.81004
## 12:112100000-112200000       76.33242       82.53985       72.12256
## 12:113600000-113700000       79.97603       80.73381       83.35509
## 12:112400000-112500000       74.75963       80.31112       73.37511
## 12:112200000-112300000       72.16454       74.96986       74.22361
## 
## [[13]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 13:48400000-48500000        146.55949      156.27270      145.56736
## 13:100400000-100500000       79.96273       75.54415       68.87058
## 13:49200000-49300000         70.94847       67.39723       76.79461
## 13:73900000-74000000         70.17138       72.05261       77.57723
## 13:56000000-56100000         69.16116       66.23338       71.90323
## 13:55100000-55200000         69.08345       66.33919       70.72930
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 13:48400000-48500000        133.87008      140.29469      131.63882
## 13:100400000-100500000       74.26159       76.16107       74.58725
## 13:49200000-49300000         68.41608       78.46666       71.63770
## 13:73900000-74000000         67.26270       62.78869       64.84970
## 13:56000000-56100000         67.13164       66.36235       66.62751
## 13:55100000-55200000         66.16175       63.24981       69.41544
## 
## [[14]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 14:3000000-3100000        169.32827      162.30353      155.93707
## 14:25900000-26000000       94.57205       95.85854       98.21883
## 14:25800000-25900000       82.44942       77.87184       73.85978
## 14:25500000-25600000       73.43516       71.10037       77.77288
## 14:25600000-25700000       77.16520       68.98429       77.47940
## 14:64200000-64300000       69.70512       69.72492       69.65320
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 14:3000000-3100000        145.22033      144.06048      149.05329
## 14:25900000-26000000       98.40381       99.48588       98.06244
## 14:25800000-25900000       73.84218       76.39163       77.17316
## 14:25500000-25600000       75.41496       76.81432       76.24385
## 14:25600000-25700000       68.12773       73.89392       70.34475
## 14:64200000-64300000       72.21697       72.89483       73.05187
## 
## [[15]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 15:74400000-74500000       84.85841       78.61247       82.95774
## 15:78500000-78600000       77.63146       83.05624       79.43595
## 15:85400000-85500000       72.81349       74.48611       83.25122
## 15:84300000-84400000       80.11815       74.48611       72.97933
## 15:79600000-79700000       74.83393       75.33254       78.94681
## 15:83700000-83800000       73.90142       73.00485       77.96854
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 15:74400000-74500000       81.02456       83.46208       73.90037
## 15:78500000-78600000       79.16343       79.73473       79.75906
## 15:85400000-85500000       74.07810       76.19950       73.25389
## 15:84300000-84400000       72.66259       79.11990       73.98118
## 15:79600000-79700000       75.65088       76.16107       70.38515
## 15:83700000-83800000       73.47520       77.16016       72.24377
## 
## [[16]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 16:3100000-3200000         84.70299       86.33617       81.49033
## 16:17900000-18000000       74.44538       73.63967       75.13154
## 16:10700000-10800000       71.25930       72.15842       75.03371
## 16:10500000-10600000       74.28996       72.68744       72.00106
## 16:18200000-18300000       73.27974       71.52359       72.58802
## 16:10600000-10700000       65.35341       70.14814       70.53365
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 16:3100000-3200000         82.02065       83.50051       91.75929
## 16:17900000-18000000       78.06248       74.04762       71.96094
## 16:10700000-10800000       71.56164       80.11899       74.78927
## 16:10500000-10600000       67.89181       72.35686       75.92061
## 16:18200000-18300000       68.99276       71.28092       69.17301
## 16:10600000-10700000       71.45679       71.70361       70.62758
## 
## [[17]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 17:40100000-40200000      216.26461      240.38698      216.00317
## 17:13700000-13800000      113.22225      116.70195      134.02371
## 17:13500000-13600000       95.97082       81.89240       92.74049
## 17:27600000-27700000       90.37576       84.00848       88.82739
## 17:3000000-3100000         81.67233       85.17232       94.50139
## 17:56600000-56700000       81.43920       78.50666       88.14260
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 17:40100000-40200000      192.22034      198.51065      189.57930
## 17:13700000-13800000      112.66371      120.00557      108.44647
## 17:13500000-13600000       86.34581       96.71918       86.74909
## 17:27600000-27700000       80.36923       84.19219       77.81963
## 17:3000000-3100000         78.92751       81.80975       76.04182
## 17:56600000-56700000       83.72450       80.69539       82.38538
## 
## [[18]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 18:36100000-36200000       71.25930       76.81380       75.71850
## 18:61100000-61200000       66.82988       69.51331       66.71837
## 18:75700000-75800000       68.61719       64.85793       70.63147
## 18:80400000-80500000       73.43516       59.14451       72.00106
## 18:75600000-75700000       69.39428       66.02178       67.79447
## 18:61000000-61100000       62.94442       68.98429       72.49020
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 18:36100000-36200000       70.98495       71.81889       68.89017
## 18:61100000-61200000       68.52093       71.66519       68.08208
## 18:75700000-75800000       68.73063       71.35778       66.70832
## 18:80400000-80500000       67.73454       69.16747       68.40532
## 18:75600000-75700000       66.55495       70.97351       67.71844
## 18:61000000-61100000       67.41998       67.70727       67.92046
## 
## [[19]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 19:6500000-6600000         77.94229       77.02541       72.97933
## 19:10200000-10300000       69.93825       77.13121       74.25109
## 19:6300000-6400000         76.23269       78.08345       72.49020
## 19:7100000-7200000         73.51287       72.26422       80.02292
## 19:5700000-5800000         75.92185       75.22674       70.04451
## 19:47200000-47300000       70.87076       71.84100       72.97933
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 19:6500000-6600000         72.11212       75.69996       71.59730
## 19:10200000-10300000       74.05188       74.54717       69.13260
## 19:6300000-6400000         71.79756       73.20224       65.41536
## 19:7100000-7200000         65.76856       69.97443       72.00134
## 19:5700000-5800000         67.47241       72.16473       68.16289
## 19:47200000-47300000       70.04128       70.62768       72.52661

10 kbp bins

x<-read.table("SRP199233.1e4_fmt.tsv",header=T,row.names=1)

x <- x[grep("X",rownames(x),invert=TRUE),]
x <- x[grep("Y",rownames(x),invert=TRUE),]
x <- x[grep("M",rownames(x),invert=TRUE),]
x <- x[grep("J",rownames(x),invert=TRUE),]
x <- x[grep("G",rownames(x),invert=TRUE),]

x <- x[which(rowSums(x)>=10),]
x <- sweep(x, 2, colSums(x), FUN="/")*1000000
mysd <- apply(x,1,sd)
mean <- apply(x,1,mean)
y <- data.frame(log10(mean),mysd/mean)
colnames(y) <- c("logMean","cv")
Rbs.9 <- cobs(y$logMean,y$cv, nknots=10,constraint="none",tau=0.99)

## qbsks2():
##  Performing general knot selection ...
## 
##  WARNING! Since the number of  10  knots selected by  AIC  reached the
##    upper bound during general knot selection, you might want to rerun
##    cobs with a larger number of knots. 
## 
##  Deleting unnecessary knots ...
## 
##  WARNING! Since the number of  10  knots selected by  AIC  reached the
##    upper bound during general knot selection, you might want to rerun
##    cobs with a larger number of knots.

## Warning in cobs(y$logMean, y$cv, nknots = 10, constraint = "none", tau = 0.99):
## The algorithm has not converged after 100 iterations

Rbs.median <- cobs(y$logMean,y$cv,nknots=10,constraint="none",tau=0.5)

## qbsks2():
##  Performing general knot selection ...
## 
##  WARNING! Since the number of  10  knots selected by  AIC  reached the
##    upper bound during general knot selection, you might want to rerun
##    cobs with a larger number of knots. 
## 
##  Deleting unnecessary knots ...
## 
##  WARNING! Since the number of  10  knots selected by  AIC  reached the
##    upper bound during general knot selection, you might want to rerun
##    cobs with a larger number of knots.

pred <- data.frame(predict(Rbs.9))

res <- mclapply(X=1:nrow(y),function(row) {
  interpolate_points(row,y,pred)
  },mc.cores=8)
y$interpolated <- unlist(res)

y$diff <- y$cv-y$interpolated
yy <- y[order(-y$diff),]
yy1 <- head(yy,20)
yy2 <- subset(y,logMean>1 & cv>0.05)
yy <- rbind(yy1,yy2)

write.table(yy,file="SRP199233.1e4_regions.tsv")

yy %>% kbl() %>% kable_paper("hover", full_width = F)

	logMean	cv	interpolated	diff
7:17030000-17040000	0.0360333	1.1039441	0.7133303	0.3906138
12:114200000-114210000	-0.4269408	1.6337781	1.2542452	0.3795330
7:31940000-31950000	-0.2426208	1.3898113	1.0115482	0.3782631
9:123730000-123740000	1.2423154	0.6424760	0.2739313	0.3685447
7:7750000-7760000	-0.3359095	1.3802584	1.1296459	0.2506126
7:25760000-25770000	-0.2793023	1.3064795	1.0566815	0.2497980
8:53410000-53420000	-0.5718049	1.7136275	1.4705958	0.2430317
16:5940000-5950000	0.3163343	0.7123142	0.4969240	0.2153902
2:71190000-71200000	0.4982121	0.6205733	0.4061030	0.2144702
10:54540000-54550000	0.5246533	0.5913321	0.3942044	0.1971277
13:120060000-120070000	0.8996092	0.4629984	0.2693580	0.1936404
9:35980000-35990000	0.3215532	0.6818176	0.4935818	0.1882358
2:50880000-50890000	-0.1283675	1.0622448	0.8792231	0.1830216
17:37760000-37770000	0.7208445	0.4891927	0.3164264	0.1727663
1:66680000-66690000	0.6877650	0.4937894	0.3287147	0.1650747
9:28820000-28830000	0.7154558	0.4827565	0.3185313	0.1642251
9:124010000-124020000	1.0831294	0.4153246	0.2571776	0.1581470
14:117600000-117610000	0.6073145	0.5148100	0.3580331	0.1567770
10:101910000-101920000	0.4385996	0.5863083	0.4296094	0.1566990
1:106620000-106630000	0.6905979	0.4828105	0.3276884	0.1551220
1:3050000-3060000	1.0343169	0.1415395	0.2569926	-0.1154531
1:26720000-26730000	1.0715981	0.0747760	0.2570761	-0.1823002
1:78580000-78590000	1.2786687	0.0866956	0.2813214	-0.1946258
1:88150000-88160000	1.4525347	0.1008891	0.3346333	-0.2337441
1:88160000-88170000	1.4842377	0.0512082	0.3473913	-0.2961830
1:88170000-88180000	1.4849623	0.0765758	0.3477135	-0.2711376
1:88180000-88190000	1.4813643	0.0811231	0.3461137	-0.2649905
1:88190000-88200000	1.3369583	0.0909673	0.2958560	-0.2048888
1:88200000-88210000	1.0819718	0.1049515	0.2571674	-0.1522159
1:88230000-88240000	1.3201181	0.1060148	0.2911207	-0.1851059
2:3050000-3060000	1.1155423	0.2149259	0.2586587	-0.0437328
2:27640000-27650000	1.0036270	0.0761909	0.2583944	-0.1822035
2:30900000-30910000	1.0115787	0.1320264	0.2580312	-0.1260048
2:98490000-98500000	4.1068263	0.0616907	4.8801484	-4.8184577
3:3000000-3010000	1.2630592	0.1309260	0.2777825	-0.1468564
3:3010000-3020000	1.2107340	0.0687979	0.2684919	-0.1996940
3:3030000-3040000	1.1425050	0.1062178	0.2603649	-0.1541471
3:3040000-3050000	1.2058171	0.0653495	0.2676450	-0.2022955
3:3050000-3060000	1.1171903	0.1103150	0.2587630	-0.1484480
3:3060000-3070000	1.0537419	0.1088068	0.2569190	-0.1481121
3:3070000-3080000	1.0035525	0.1378395	0.2583978	-0.1205583
3:93670000-93680000	1.0083418	0.1395589	0.2581790	-0.1186201
3:93700000-93710000	1.0253920	0.0698928	0.2574002	-0.1875075
3:93720000-93730000	1.0394782	0.1199016	0.2567934	-0.1368918
4:3050000-3060000	1.4034462	0.1424276	0.3165090	-0.1740814
4:3060000-3070000	1.4334730	0.1210423	0.3271963	-0.2061540
4:3080000-3090000	1.7249524	0.1273644	0.4785845	-0.3512202
4:3220000-3230000	1.1399841	0.0854510	0.2602054	-0.1747544
4:62420000-62430000	1.0405516	0.1278412	0.2568029	-0.1289616
4:62430000-62440000	1.0173284	0.1128875	0.2577685	-0.1448810
4:118400000-118410000	1.3255264	0.1585187	0.2926415	-0.1341228
4:136920000-136930000	1.0032893	0.1949385	0.2584098	-0.0634712
4:145130000-145140000	1.0127545	0.1569242	0.2579775	-0.1010532
4:145160000-145170000	1.2448074	0.0850306	0.2743605	-0.1893299
4:145170000-145180000	1.0732868	0.0772720	0.2570910	-0.1798190
4:145270000-145280000	1.0339035	0.0921447	0.2570114	-0.1648668
4:145280000-145290000	1.2004059	0.1018341	0.2668633	-0.1650292
4:145300000-145310000	1.0560702	0.1105148	0.2569395	-0.1464247
4:145990000-146000000	1.1110493	0.0857075	0.2583744	-0.1726669
4:146480000-146490000	1.2904871	0.1057822	0.2840008	-0.1782185
4:146530000-146540000	1.0702147	0.1129153	0.2570640	-0.1441487
4:146540000-146550000	1.1086665	0.0729052	0.2582236	-0.1853184
4:146560000-146570000	1.3294246	0.0595061	0.2937376	-0.2342315
4:146570000-146580000	1.2238242	0.0707822	0.2707465	-0.1999643
4:146600000-146610000	1.1302364	0.1051576	0.2595886	-0.1544310
4:146610000-146620000	1.0120942	0.0889889	0.2580076	-0.1690187
4:147420000-147430000	1.2501074	0.0942106	0.2752734	-0.1810628
4:147480000-147490000	1.3505965	0.0741320	0.2996910	-0.2255590
4:147600000-147610000	1.3238458	0.0882373	0.2921689	-0.2039316
4:147610000-147620000	1.0823340	0.1111105	0.2571706	-0.1460602
4:156560000-156570000	1.1302299	0.0913560	0.2595881	-0.1682322
5:26270000-26280000	1.0965269	0.0733018	0.2574554	-0.1841536
5:125110000-125120000	1.0070011	0.0873849	0.2582403	-0.1708554
5:145570000-145580000	1.1296581	0.1235072	0.2595520	-0.1360448
5:145580000-145590000	1.0090356	0.1191148	0.2581473	-0.1390325
5:146190000-146200000	1.0873939	0.1071621	0.2572152	-0.1500531
6:29740000-29750000	1.1482865	0.1750732	0.2607308	-0.0856576
7:11740000-11750000	1.1490924	0.1031862	0.2608207	-0.1576344
7:63720000-63730000	1.0750784	0.1609714	0.2571068	-0.0961353
7:63730000-63740000	1.1856495	0.1580365	0.2651256	-0.1070890
7:141540000-141550000	1.0051323	0.1220476	0.2583256	-0.1362780
8:19750000-19760000	1.0472848	0.0959122	0.2568621	-0.1609499
9:3000000-3010000	2.6624678	0.0594039	1.5379283	-1.4785244
9:3010000-3020000	1.1116462	0.1478245	0.2584122	-0.1105877
9:3030000-3040000	1.4304085	0.1104869	0.3260007	-0.2155138
9:24450000-24460000	1.0222399	0.1161994	0.2575442	-0.1413448
9:123720000-123730000	1.1930203	0.2659023	0.2659935	-0.0000912
9:123730000-1237400001	1.2423154	0.6424760	0.2739313	0.3685447
9:124010000-1240200001	1.0831294	0.4153246	0.2571776	0.1581470
9:124020000-124030000	1.0297864	0.4002630	0.2571995	0.1430635
10:3060000-3070000	1.2823173	0.1470487	0.2821486	-0.1350999
10:57980000-57990000	1.1576015	0.0916038	0.2618227	-0.1702189
10:58010000-58020000	1.0479631	0.0986515	0.2568681	-0.1582166
10:74770000-74780000	1.0070956	0.1204115	0.2582359	-0.1378244
10:81080000-81090000	1.0032012	0.1783618	0.2584138	-0.0800520
10:81320000-81330000	1.0020301	0.1424046	0.2584673	-0.1160628
10:128270000-128280000	1.0988986	0.0804620	0.2576055	-0.1771435
11:3050000-3060000	1.2375892	0.1083057	0.2731173	-0.1648116
11:3130000-3140000	1.9673648	0.0550096	0.6684278	-0.6134182
11:74270000-74280000	1.0073982	0.2633508	0.2582221	0.0051287
11:108900000-108910000	1.2633352	0.0849424	0.2778451	-0.1929027
11:115680000-115690000	1.0020469	0.1339694	0.2584665	-0.1244971
11:119390000-119400000	1.0357773	0.1108260	0.2569258	-0.1460999
12:3150000-3160000	1.3901469	0.1352009	0.3120448	-0.1768440
12:67100000-67110000	1.2827302	0.1025963	0.2822422	-0.1796459
12:74850000-74860000	1.0276929	0.1382781	0.2572951	-0.1190170
12:113650000-113660000	1.1060277	0.1150256	0.2580566	-0.1430311
12:114790000-114800000	1.0454694	0.1022528	0.2568462	-0.1545934
12:115570000-115580000	1.2545311	0.1163261	0.2760353	-0.1597092
12:115580000-115590000	1.3490399	0.1097615	0.2992533	-0.1894918
12:115600000-115610000	1.0811865	0.0982887	0.2571605	-0.1588718
12:115620000-115630000	1.0485069	0.0604939	0.2568729	-0.1963790
12:115770000-115780000	1.0599135	0.1361010	0.2569733	-0.1208723
12:115780000-115790000	1.1290625	0.1052790	0.2595143	-0.1542353
13:48400000-48410000	1.3158310	0.1244950	0.2899152	-0.1654201
13:48410000-48420000	1.7616365	0.0874533	0.5034673	-0.4160140
13:48420000-48430000	1.5138950	0.1137102	0.3605778	-0.2468675
13:100420000-100430000	1.0947174	0.0621705	0.2573409	-0.1951704
13:100430000-100440000	1.0600517	0.0978623	0.2569745	-0.1591122
13:100470000-100480000	1.0546832	0.0931536	0.2569273	-0.1637736
14:3050000-3060000	2.1517725	0.0720648	0.8524559	-0.7803912
14:25870000-25880000	1.0723757	0.0708794	0.2570830	-0.1862036
14:25880000-25890000	1.1239930	0.1048677	0.2591935	-0.1543258
14:25890000-25900000	1.0830837	0.0954227	0.2571772	-0.1617545
14:25930000-25940000	1.0449621	0.1231236	0.2568417	-0.1337181
14:25940000-25950000	1.0128926	0.0740166	0.2579711	-0.1839545
14:25970000-25980000	1.0163697	0.0882185	0.2578123	-0.1695938
14:26000000-26010000	1.0477955	0.1490382	0.2568666	-0.1078285
14:43130000-43140000	1.0539837	0.1025335	0.2569211	-0.1543876
15:60010000-60020000	1.0650194	0.1832882	0.2570182	-0.0737301
15:74950000-74960000	1.1349056	0.1642137	0.2598840	-0.0956703
16:3050000-3060000	1.4782379	0.0680361	0.3447236	-0.2766875
16:3060000-3070000	1.0780704	0.0546030	0.2571331	-0.2025301
16:3080000-3090000	1.0239264	0.0640420	0.2574672	-0.1934252
16:3140000-3150000	1.0946425	0.1593219	0.2573362	-0.0980143
16:3150000-3160000	1.1745218	0.0687724	0.2638152	-0.1950427
16:3160000-3170000	1.1470615	0.0939146	0.2606533	-0.1667387
16:3460000-3470000	1.0054017	0.1492220	0.2583133	-0.1090913
16:3470000-3480000	1.0120201	0.1324063	0.2580110	-0.1256047
16:10790000-10800000	1.0769525	0.0875950	0.2571233	-0.1695282
16:57210000-57220000	1.0534616	0.2817003	0.2569165	0.0247838
17:3050000-3060000	1.0540755	0.1063578	0.2569219	-0.1505641
17:3060000-3070000	1.2727091	0.1077770	0.2799703	-0.1721932
17:3070000-3080000	1.3841327	0.1371210	0.3100260	-0.1729050
17:3080000-3090000	1.3832268	0.1030983	0.3097220	-0.2066237
17:13410000-13420000	1.0055431	0.1102182	0.2583068	-0.1480887
17:13430000-13440000	1.1671447	0.0545381	0.2629465	-0.2084084
17:13440000-13450000	1.0975126	0.0967866	0.2575178	-0.1607312
17:13450000-13460000	1.0375367	0.1370844	0.2568455	-0.1197610
17:13520000-13530000	1.6751708	0.1124897	0.4467500	-0.3342602
17:13770000-13780000	1.8153491	0.1364580	0.5424999	-0.4060419
17:13810000-13820000	1.5061378	0.1011461	0.3571287	-0.2559826
17:23730000-23740000	1.0819914	0.1153672	0.2571676	-0.1418004
17:27600000-27610000	1.0064847	0.2396170	0.2582638	-0.0186469
17:36370000-36380000	1.0427116	0.1522192	0.2568219	-0.1046027
17:36540000-36550000	1.2622268	0.0970298	0.2775937	-0.1805639
17:40150000-40160000	2.2715814	0.1048310	0.9900289	-0.8851979
17:56690000-56700000	1.0204657	0.2672525	0.2576252	0.0096272
17:56700000-56710000	1.0243210	0.0603993	0.2574491	-0.1970499
19:3310000-3320000	1.0113073	0.2189505	0.2580436	-0.0390931
19:6790000-6800000	1.1135937	0.2192099	0.2585354	-0.0393255
19:58100000-58110000	1.3328593	0.1465127	0.2947034	-0.1481907

plot(y$logMean,y$cv,pch=18,cex=0.5,xlab="log10(mean)",ylab="CV")
lines(predict(Rbs.9), col = "red", lwd = 1.0)
lines(predict(Rbs.median), col = "blue", lwd = 1.0)
points(yy$logMean,yy$cv)

#text(yy$logMean,yy$cv+0.02,labels=rownames(yy),cex=0.8)

plot(y$logMean,y$cv,pch=18,cex=0.5,xlab="log10(mean)",ylab="CV",xlim=c(0,4.5),ylim=c(0,1))
lines(predict(Rbs.9), col = "red", lwd = 1.0)
lines(predict(Rbs.median), col = "blue", lwd = 1.0)
points(yy$logMean,yy$cv)

#text(yy$logMean,yy$cv+0.02,labels=rownames(yy),cex=0.8)

my_palette <- colorRampPalette(c("blue", "white", "red"))(n = 25)
zz <- x[which(rownames(x) %in% rownames(yy)),]
heatmap.2(as.matrix(zz),margin=c(8, 22),cexRow=0.65,trace="none",
  cexCol=0.8,col=my_palette,scale="row")

heatmap.2(cor(t(zz)),trace="none",scale="none",margins=c(12,12),
  cexRow=0.8, cexCol=0.8)

for (i in 1:19){
mychr=as.character(i)
regex=paste("^",mychr,":",sep="")
chr <- x[grep(regex,rownames(x)),]
mymax = max(chr)
plot(chr[,1], xaxt = "n", pch=19, col="gray",
  ylim=c(0,mymax),ylab="RPM of 10 kbp bins of chr",main=mychr)
axis(1, at=chr[,1], labels=rownames(chr), xlab="chr", las=1)
points( chr[,1], xaxt = "n", las=1, pch=19, col="gray"  )
points( chr[,2], xaxt = "n", las=1, pch=19, col="lightblue"  )
points( chr[,3], xaxt = "n", las=1, pch=19, col="lightgreen"  )
points( chr[,4], xaxt = "n", las=1, pch=19, col="pink" )
points( chr[,5], xaxt = "n", las=1, pch=19, col="orange" )
points( chr[,6], xaxt = "n", las=1, pch=19, col="black" )
grid()
}

lapply(1:19,function(i){
  mychr=as.character(i)
  regex=paste("^",mychr,":",sep="")
  chr <- x[grep(regex,rownames(x)),]
  mymedian <- median(rowMeans(chr))
  mymax <- max(rowMeans(chr))
  rat <- mymax / mymedian
  return(c(mymax,mymedian,rat))
})

## [[1]]
## [1] 30.546557  3.791809  8.055932
## 
## [[2]]
## [1] 12788.697944     4.101051  3118.395398
## 
## [[3]]
## [1] 18.325642  3.585453  5.111109
## 
## [[4]]
## [1] 53.082624  3.958825 13.408682
## 
## [[5]]
## [1] 13.479013  4.219938  3.194126
## 
## [[6]]
## [1] 769.705787   3.851269 199.857688
## 
## [[7]]
## [1] 15.333788  4.385763  3.496265
## 
## [[8]]
## [1] 11.150256  4.122314  2.704854
## 
## [[9]]
## [1] 459.692947   4.440531 103.522062
## 
## [[10]]
## [1] 19.156552  3.866809  4.954098
## 
## [[11]]
## [1] 146.644265   4.741329  30.928939
## 
## [[12]]
## [1] 24.555393  3.885207  6.320227
## 
## [[13]]
## [1] 57.761239  3.987906 14.484101
## 
## [[14]]
## [1] 141.831439   3.738383  37.939250
## 
## [[15]]
## [1] 13.642865  3.976973  3.430464
## 
## [[16]]
## [1] 30.077236  3.725684  8.072944
## 
## [[17]]
## [1] 186.887993   4.207523  44.417585
## 
## [[18]]
## [1] 8.923642 3.933637 2.268548
## 
## [[19]]
## [1] 21.520843  4.349001  4.948456

lapply(1:19,function(i){
  mychr=as.character(i)
  regex=paste("^",mychr,":",sep="")
  chr <- x[grep(regex,rownames(x)),]
  top <- head(chr[order(-rowMeans(chr)),])
  return(top)
})

## [[1]]
##                     SRX5884275.bam SRX5884276.bam SRX5884277.bam SRX5884278.bam
## 1:88170000-88180000       34.97514       30.53884       30.20736       29.09741
## 1:88160000-88170000       32.38730       31.82019       30.79967       28.83288
## 1:88180000-88190000       31.99520       28.61681       32.97144       28.33029
## 1:88150000-88160000       28.07422       23.70497       26.65356       29.67935
## 1:88140000-88150000       27.99580       26.80157       28.13431       25.63217
## 1:88210000-88220000       23.91798       24.34565       24.77794       24.60053
##                     SRX5884279.bam SRX5884280.bam
## 1:88170000-88180000       30.24641       28.21418
## 1:88160000-88170000       30.63418       28.49959
## 1:88180000-88190000       32.49550       27.35797
## 1:88150000-88160000       31.56484       30.41587
## 1:88140000-88150000       28.19120       28.54036
## 1:88210000-88220000       22.21948       22.66920
## 
## [[2]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 2:98490000-98500000      13874.54573   13093.686747   11833.192168
## 2:3050000-3060000           13.17449      18.045677       9.476820
## 2:30900000-30910000         10.42981      11.852486      11.846025
## 2:27640000-27650000         10.27297       8.969449      10.957573
## 2:179830000-179840000       10.27297      10.250799      12.142176
## 2:31270000-31280000         11.60610      10.357578       8.687085
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 2:98490000-98500000     13014.449745   11884.743972   13031.569308
## 2:3050000-3060000          12.776407      12.990444      11.823864
## 2:30900000-30910000         8.993744       9.733139       8.765968
## 2:27640000-27650000        10.316353       9.345364      10.641477
## 2:179830000-179840000       9.152457       8.957590       7.991301
## 2:31270000-31280000         9.893118      10.237245       7.909757
## 
## [[3]]
##                   SRX5884275.bam SRX5884276.bam SRX5884277.bam SRX5884278.bam
## 3:3000000-3010000       20.70278       20.28804       18.26262       16.08293
## 3:3010000-3020000       15.76234       17.93890       14.80753       15.63324
## 3:3040000-3050000       17.33073       16.12365       15.39983       14.36354
## 3:3030000-3040000       13.72343       12.06604       15.89342       13.94030
## 3:3050000-3060000       12.78240       12.92028       14.80753       12.08865
## 3:3060000-3070000       10.97874       10.14402       11.54987       10.44861
##                   SRX5884279.bam SRX5884280.bam
## 3:3000000-3010000       19.77650       14.84099
## 3:3010000-3020000       16.24775       17.08344
## 3:3040000-3050000       16.44164       16.71650
## 3:3030000-3040000       15.16198       12.51699
## 3:3050000-3060000       14.77421       11.21228
## 3:3060000-3070000       13.61088       11.17151
## 
## [[4]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 4:3080000-3090000           51.60010       57.66074       62.38907
## 4:3060000-3070000           31.13258       24.34565       30.20736
## 4:3050000-3060000           26.11373       24.55920       32.08299
## 4:147480000-147490000       24.54534       19.86092       21.61900
## 4:146560000-146570000       19.84016       22.74396       22.70488
## 4:118400000-118410000       20.78120       23.81175       25.86382
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 4:3080000-3090000           47.87846       55.21908       43.74830
## 4:3060000-3070000           23.11921       28.50142       25.48246
## 4:3050000-3060000           23.06631       24.19713       21.89453
## 4:147480000-147490000       23.01340       23.61546       21.85376
## 4:146560000-146570000       21.74370       21.05615       20.01902
## 4:118400000-118410000       19.01912       21.05615       16.43109
## 
## [[5]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 5:145570000-145580000      14.899725      15.162640      12.339610
## 5:26270000-26280000        12.782396      13.240615      11.253724
## 5:146190000-146200000      14.272368      13.347394      11.056290
## 5:145580000-145590000      11.527682       9.396565      11.056290
## 5:125110000-125120000       9.959290      10.464357       8.588368
## 5:35230000-35240000         9.410353      10.891474      11.155007
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 5:145570000-145580000      14.363538      10.857685      13.250882
## 5:26270000-26280000        12.406076      11.633233      13.617829
## 5:146190000-146200000      11.824128      11.865898      11.008425
## 5:145580000-145590000      11.109919       9.771916       8.399020
## 5:125110000-125120000      10.025379      11.051572      10.886109
## 5:35230000-35240000         8.782126       9.694361       9.948354
## 
## [[6]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 6:103620000-103630000     802.154155     791.340296     780.159487
## 6:29740000-29750000        17.017055      13.347394      17.374171
## 6:88880000-88890000         9.567192      11.959265       9.575537
## 6:113870000-113880000       6.665667       9.823682      13.326779
## 6:115900000-115910000      10.665066       9.396565       9.970405
## 6:100430000-100440000       9.567192      10.037240       9.180670
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 6:103620000-103630000     753.252488     733.785590     757.542708
## 6:29740000-29750000        12.115102      12.292450      12.272355
## 6:88880000-88890000         8.491152       8.375928       8.317476
## 6:113870000-113880000       8.015013       9.655584       8.765968
## 6:115900000-115910000       7.697587       8.957590       9.459091
## 6:100430000-100440000       9.522787       9.267809       8.235933
## 
## [[7]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 7:63730000-63740000        16.232859      14.842302      16.090851
## 7:11740000-11750000        13.880270      16.977885      13.820363
## 7:63720000-63730000        10.900325      10.571136      15.695984
## 7:141540000-141550000       9.018255      10.144019      12.438327
## 7:34730000-34740000        10.351388       9.396565       9.772971
## 7:144660000-144670000       9.096674      10.784694      12.142176
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 7:63730000-63740000        11.559606      18.884616      14.392496
## 7:11740000-11750000        13.702233      13.106776      13.087794
## 7:63720000-63730000        11.824128      11.323014      11.008425
## 7:141540000-141550000      10.263449       9.267809       9.581407
## 7:34730000-34740000         9.655048      11.284236       9.092143
## 7:144660000-144670000       8.808578       9.733139       8.929056
## 
## [[8]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 8:19750000-19760000         9.488772      12.599940       11.84603
## 8:121030000-121040000       7.841961       9.503345       11.05629
## 8:123040000-123050000       8.704576      10.677915       13.32678
## 8:123020000-123030000      10.508227       7.474541       10.95757
## 8:71160000-71170000         9.724031       9.183007       10.56271
## 8:122610000-122620000       9.410353       7.688099       11.45116
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 8:19750000-19760000        10.924753      11.400569      10.641477
## 8:121030000-121040000      10.104736      11.982230       8.317476
## 8:123040000-123050000       9.707953       8.802480       6.931230
## 8:123020000-123030000       9.522787       9.616806       9.826038
## 8:71160000-71170000        10.104736       9.267809       8.113617
## 8:122610000-122620000      10.157640       9.422919       8.480564
## 
## [[9]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 9:3000000-3010000          478.75170      468.97404      415.79549
## 9:35210000-35220000        304.11123      290.22574      268.41119
## 9:3020000-3030000          179.73774      165.61446      158.93417
## 9:3030000-3040000           29.01525       31.92697       25.76511
## 9:123730000-123740000       30.26997       22.31684       29.51635
## 9:123720000-123730000       18.97754       18.79313       20.03953
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 9:3000000-3010000         472.012832     436.866694     485.756933
## 9:35210000-35220000       291.608914     271.829889     289.073078
## 9:3020000-3030000         170.457896     163.757150     173.892338
## 9:3030000-3040000          23.912777      25.011452      26.012500
## 9:123730000-123740000       7.988561       6.049281       8.684424
## 9:123720000-123730000      13.490616      11.594456      10.682249
## 
## [[10]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 10:3060000-3070000          17.252313      18.152456       22.90232
## 10:57980000-57990000        13.488172      15.269419       14.11651
## 10:128270000-128280000      14.507627      11.959265       12.14218
## 10:58010000-58020000        10.900325      12.172823       10.76014
## 10:74770000-74780000        11.998200       9.183007       10.26656
## 10:81080000-81090000         7.685121      10.677915       12.83319
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 10:3060000-3070000          15.289364       19.81527      21.527586
## 10:57980000-57990000        13.649329       16.59675      13.128566
## 10:128270000-128280000      12.273815       12.71900      11.742320
## 10:58010000-58020000        10.131188       10.19847      12.843162
## 10:74770000-74780000         9.364074       11.20668       8.969828
## 10:81080000-81090000         8.808578       10.85768       9.581407
## 
## [[11]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 11:3140000-3150000         152.212456      150.34505      148.47018
## 11:3130000-3140000          94.809304       97.91648       98.42073
## 11:108900000-108910000      19.369643       20.28804       17.57160
## 11:3050000-3060000          15.605502       15.37620       20.53311
## 11:119390000-119400000       9.959290       13.02706       11.35244
## 11:74270000-74280000         9.645612       14.94908       11.45116
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 11:3140000-3150000         144.137969      141.30501     143.394925
## 11:3130000-3140000          85.837348       90.73922      88.842065
## 11:108900000-108910000      17.855226       15.89875      19.040498
## 11:3050000-3060000          17.299731       17.91518      16.961128
## 11:119390000-119400000       9.840214       10.78013      10.192986
## 11:74270000-74280000         7.538873        8.80248       8.643652
## 
## [[12]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 12:3150000-3160000           28.07422       29.36427       21.42156
## 12:115580000-115590000       25.95689       22.42362       18.26262
## 12:115560000-115570000       19.76174       21.14227       21.52028
## 12:67100000-67110000         17.48757       21.99651       16.78187
## 12:115570000-115580000       18.89913       14.84230       15.79470
## 12:115780000-115790000       10.74349       14.62874       14.31395
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 12:3150000-3160000           23.25147       22.10314       23.11769
## 12:115580000-115590000       22.64307       22.72358       22.01685
## 12:115560000-115570000       22.27274       21.28882       22.26148
## 12:67100000-67110000         19.28364       20.78471       18.71432
## 12:115570000-115580000       19.41591       19.66016       19.20359
## 12:115780000-115790000       13.17319       13.95988       13.94400
## 
## [[13]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 13:48410000-48420000         59.59890       63.85393      63.080085
## 13:48420000-48430000         35.75934       34.38289      34.156040
## 13:48400000-48410000         22.74169       24.45243      17.078020
## 13:100420000-100430000       12.54714       13.88129      12.240893
## 13:100430000-100440000       11.76294       11.53215       9.476820
## 13:100470000-100480000       11.84136       11.42537       9.279387
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 13:48410000-48420000         52.95728       53.70676       53.37047
## 13:48420000-48430000         30.65809       34.97726       25.97173
## 13:48400000-48410000         19.65398       19.97038       20.26366
## 13:100420000-100430000       11.58606       12.17612       12.19081
## 13:100430000-100440000       11.34799       12.91289       11.86464
## 13:100470000-100480000       11.42734       12.25367       11.82386
## 
## [[14]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 14:3050000-3060000        156.76079      148.74336      145.70611
## 14:25880000-25890000       13.25291       15.48298       13.32678
## 14:25890000-25900000       13.01765       10.46436       11.94474
## 14:25870000-25880000       12.62556       11.10503       12.83319
## 14:25960000-25970000       11.76294       11.74571       11.54987
## 14:43130000-43140000       12.07662       10.03724       12.83319
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 14:3050000-3060000        131.46737      131.76576      136.54524
## 14:25880000-25890000       11.08347       13.18433       13.49551
## 14:25890000-25900000       11.03056       13.14555       13.04702
## 14:25870000-25880000       11.42734       10.78013       12.10927
## 14:25960000-25970000       11.69187       11.32301       11.94618
## 14:43130000-43140000       11.53315       11.59446        9.86681
## 
## [[15]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 15:74950000-74960000        14.037110      16.337210      16.189568
## 15:60010000-60020000         9.645612      15.589756      10.760140
## 15:83720000-83730000        10.037710       9.396565      10.463989
## 15:84830000-84840000         9.096674      10.464357       9.970405
## 15:101380000-101390000       9.488772      10.571136       8.193501
## 15:85410000-85420000        11.214004       7.367761      13.622929
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 15:74950000-74960000        12.141554      12.021008      11.130741
## 15:60010000-60020000        12.062197      11.439346      10.192986
## 15:83720000-83730000         9.681501       9.539251      10.233758
## 15:84830000-84840000        10.316353       9.500474       9.459091
## 15:101380000-101390000       8.861483      10.663797       9.785266
## 15:85410000-85420000         8.570509       7.949376       8.276705
## 
## [[16]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 16:3050000-3060000         33.01465       30.96595       28.82533
## 16:3150000-3160000         13.64501       15.69654       14.41266
## 16:3160000-3170000         12.78240       14.20163       12.14218
## 16:3140000-3150000         15.68392       10.99825       11.54987
## 16:3060000-3070000         12.46872       10.89147       11.84603
## 16:10790000-10800000       10.42981       11.42537       11.74731
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 16:3050000-3060000         28.88579       31.33218       27.43952
## 16:3150000-3160000         14.07256       15.74364       16.10492
## 16:3160000-3170000         15.63324       14.58032       14.84099
## 16:3140000-3150000         10.34281       12.25367       13.78092
## 16:3060000-3070000         11.61251       12.60267       12.39467
## 16:10790000-10800000       12.06220       13.57211       12.39467
## 
## [[17]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 17:40150000-40160000      194.24537      219.96505      192.00433
## 17:13770000-13780000       64.77459       64.28105       81.83629
## 17:13520000-13530000       51.28642       42.81844       55.18273
## 17:13810000-13820000       32.46572       26.90835       36.82140
## 17:3070000-3080000         25.01585       25.09310       28.92405
## 17:3080000-3090000         24.15324       23.27786       29.02276
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 17:40150000-40160000      170.45790      177.36803      167.28728
## 17:13770000-13780000       58.19481       66.27065       56.83609
## 17:13520000-13530000       41.31832       48.58814       44.80837
## 17:13810000-13820000       30.71099       32.30161       33.22913
## 17:3070000-3080000         21.66434       25.28289       19.32590
## 17:3080000-3090000         21.87596       23.18891       23.48464
## 
## [[18]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 18:82200000-82210000      10.037710       8.755890       8.390935
## 18:3110000-3120000        11.292423       7.581320       8.588368
## 18:35970000-35980000       9.959290       9.610124       8.687085
## 18:32130000-32140000       7.293023       8.542332      12.635760
## 18:82230000-82240000       9.096674       7.794878      10.069122
## 18:36100000-36110000       7.998800       8.649111      10.167838
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 18:82200000-82210000       8.253082      10.276023       7.828213
## 18:3110000-3120000         9.073100       8.569815       8.317476
## 18:35970000-35980000       7.221447       8.763703       7.502038
## 18:32130000-32140000       7.750491       8.220818       7.175862
## 18:82230000-82240000       8.729222       8.802480       6.808915
## 18:36100000-36110000       8.094369       8.143263       7.909757
## 
## [[19]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 19:58100000-58110000      26.584247      18.793131      22.803599
## 19:6790000-6800000        17.409153      12.813498      14.708815
## 19:3310000-3320000         9.645612      13.027057      13.030628
## 19:6360000-6370000        10.429808      11.532148      11.648592
## 19:10260000-10270000       8.312478      11.959265      11.451158
## 19:5910000-5920000        10.586647       8.115216       9.378103
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 19:58100000-58110000      21.690794      21.599037      17.654251
## 19:6790000-6800000        10.633779      12.912889       9.459091
## 19:3310000-3320000         9.311170       7.639157       8.929056
## 19:6360000-6370000         8.596961       9.461697       6.931230
## 19:10260000-10270000       9.020196       7.794266       7.461266
## 19:5910000-5920000        10.263449       7.290160       9.703723

1 kbp bins

x <- read.table("SRP199233.1e3_fmt.tsv",header=T,row.names=1)

x <- x[grep("X",rownames(x),invert=TRUE),]
x <- x[grep("Y",rownames(x),invert=TRUE),]
x <- x[grep("M",rownames(x),invert=TRUE),]
x <- x[grep("J",rownames(x),invert=TRUE),]
x <- x[grep("G",rownames(x),invert=TRUE),]

x <- x[which(rowSums(x)>=6),]
x <- sweep(x, 2, colSums(x), FUN="/")*1000000
mysd <- apply(x,1,sd)
mean <- apply(x,1,mean)
y <- data.frame(log10(mean),mysd/mean)
colnames(y) <- c("logMean","cv")

yy <- subset(y,cv > 0.2 & logMean > 0.3)

write.table(yy,file="SRP199233.1e3_regions.tsv")

yy %>% kbl() %>% kable_paper("hover", full_width = F)

	logMean	cv
1:26726000-26727000	0.5263386	0.2023906
1:26727000-26728000	0.3671018	0.2957206
1:85224000-85225000	0.3457924	0.4819187
1:88139000-88140000	0.4465684	0.2062768
1:88141000-88142000	0.5864733	0.2283613
1:88143000-88144000	0.3150223	0.4205346
1:88144000-88145000	0.3806144	0.3521415
1:88146000-88147000	0.3868203	0.2343544
1:88147000-88148000	0.3611945	0.2528010
1:88149000-88150000	0.3166738	0.2715215
1:88154000-88155000	0.4101979	0.2164641
1:88155000-88156000	0.3187685	0.2919325
1:88156000-88157000	0.3821539	0.3988284
1:88157000-88158000	0.5125009	0.3070781
1:88161000-88162000	0.4901084	0.2371089
1:88162000-88163000	0.5284901	0.2444235
1:88164000-88165000	0.4797259	0.3430917
1:88165000-88166000	0.5144885	0.2832921
1:88166000-88167000	0.5273474	0.2128523
1:88168000-88169000	0.4643874	0.2836218
1:88171000-88172000	0.3746606	0.4463203
1:88173000-88174000	0.4881784	0.2382137
1:88175000-88176000	0.4979420	0.3061693
1:88176000-88177000	0.4816976	0.3121596
1:88178000-88179000	0.5083114	0.2932264
1:88179000-88180000	0.3888516	0.3207755
1:88180000-88181000	0.5493392	0.2829513
1:88182000-88183000	0.4594894	0.3004601
1:88183000-88184000	0.6493227	0.2496315
1:88184000-88185000	0.3650176	0.2215592
1:88186000-88187000	0.3217339	0.2194689
1:88187000-88188000	0.5073230	0.3062946
1:88191000-88192000	0.4610506	0.2182192
1:88197000-88198000	0.4436081	0.2179953
1:88199000-88200000	0.4422926	0.3054943
1:88200000-88201000	0.3811872	0.3030465
1:88211000-88212000	0.3734144	0.2246811
1:88212000-88213000	0.5500500	0.2357880
1:88214000-88215000	0.4133140	0.2687079
1:88216000-88217000	0.4161368	0.3710509
1:88217000-88218000	0.3025685	0.3373660
1:88218000-88219000	0.4377933	0.2491022
1:88222000-88223000	0.3898524	0.2760664
1:88224000-88225000	0.3457363	0.2405953
1:88225000-88226000	0.4657256	0.5093220
1:88226000-88227000	0.4814122	0.2303979
1:88227000-88228000	0.3707642	0.3283760
1:88228000-88229000	0.4515803	0.2562027
1:88229000-88230000	0.4393862	0.2498316
1:88230000-88231000	0.3396387	0.2004791
1:88234000-88235000	0.3232487	0.2699256
1:88235000-88236000	0.3349042	0.3154197
1:88236000-88237000	0.3265340	0.3414923
1:88237000-88238000	0.3394314	0.3917285
1:133522000-133523000	0.4596481	0.3549663
2:3050000-3051000	0.8747341	0.2372579
3:3000000-3001000	0.3197739	0.3365244
3:3002000-3003000	0.4804411	0.2249042
3:3007000-3008000	0.4753203	0.2509223
3:3019000-3020000	0.3239539	0.3475607
3:3021000-3022000	0.3267699	0.2115578
3:3039000-3040000	0.6524386	0.2332658
3:3044000-3045000	0.3573411	0.2501687
3:3055000-3056000	0.4374936	0.2001870
3:56483000-56484000	0.5450615	0.2118596
3:106078000-106079000	0.3172701	0.4095553
4:3051000-3052000	0.3859916	0.3680367
4:3053000-3054000	0.4868701	0.2494278
4:3054000-3055000	0.3169470	0.3200785
4:3059000-3060000	0.3471502	0.2369251
4:3064000-3065000	0.5486090	0.2573194
4:3065000-3066000	0.4001479	0.3665894
4:3068000-3069000	0.4730580	0.2500114
4:3080000-3081000	0.7406716	0.2510327
4:3081000-3082000	0.9518313	0.2232120
4:3084000-3085000	0.7804400	0.2619006
4:3090000-3091000	0.4998002	0.3046484
4:3225000-3226000	0.3839216	0.3117556
4:3226000-3227000	0.3917323	0.2350098
4:3229000-3230000	0.3589275	0.2414284
4:20191000-20192000	0.4259404	0.2513050
4:118404000-118405000	0.3636487	0.4587762
4:131237000-131238000	0.3424938	0.3838720
4:145166000-145167000	0.4837666	0.2453238
4:145167000-145168000	0.3111625	0.2255648
4:145284000-145285000	0.3210452	0.3635893
4:145285000-145286000	0.3596831	0.3167893
4:145294000-145295000	0.3125393	0.2147276
4:145306000-145307000	0.3554331	0.3098261
4:146481000-146482000	0.3137706	0.2446398
4:146483000-146484000	0.4123668	0.2821324
4:146485000-146486000	0.4713829	0.2255121
4:146486000-146487000	0.3932375	0.2984916
4:146503000-146504000	0.3215382	0.4401590
4:146528000-146529000	0.3230428	0.2165852
4:146529000-146530000	0.3467389	0.2819931
4:146541000-146542000	0.3382787	0.3559217
4:146542000-146543000	0.5049007	0.3543995
4:146566000-146567000	0.3829520	0.2767458
4:146569000-146570000	0.5100686	0.2758507
4:146826000-146827000	0.3001363	0.2129272
4:147009000-147010000	0.3088220	0.3534610
4:147180000-147181000	0.5018582	0.2544044
4:147420000-147421000	0.4937913	0.3263862
4:147421000-147422000	0.3646795	0.2693492
4:147422000-147423000	0.4442932	0.3582010
4:147483000-147484000	0.3750634	0.2899344
4:147559000-147560000	0.3503436	0.2541490
4:147583000-147584000	0.3420081	0.3366127
4:147604000-147605000	0.5590267	0.2379178
4:147608000-147609000	0.3806338	0.2148367
4:156498000-156499000	0.3114972	0.2128097
5:26212000-26213000	0.3332640	0.2571975
5:104479000-104480000	0.3218380	0.4189062
5:145575000-145576000	0.3082802	0.3086627
5:146197000-146198000	0.7366872	0.2692930
5:146198000-146199000	0.4841519	0.2277245
6:29748000-29749000	0.9397913	0.2309727
6:87434000-87435000	0.4453065	0.3032236
6:121287000-121288000	0.3022131	0.4511161
7:59419000-59420000	0.5072052	0.3639164
7:63723000-63724000	0.4473893	0.2580819
7:63730000-63731000	0.3595487	0.2802548
8:14356000-14357000	0.5415129	0.2566198
8:21054000-21055000	0.3490336	0.4098645
8:21437000-21438000	0.3576661	0.2796699
8:74345000-74346000	0.4264573	0.3379868
9:3018000-3019000	0.4656034	0.2907182
9:3020000-3021000	0.5754353	0.2333341
9:3035000-3036000	0.3699246	0.3584200
9:107407000-107408000	0.3798817	0.2911331
9:123702000-123703000	0.9543044	0.3462669
9:123721000-123722000	0.7789825	0.2437707
9:123728000-123729000	0.4354049	0.7081383
9:123729000-123730000	0.3715297	0.6523717
9:123730000-123731000	0.4867688	0.7712962
9:123731000-123732000	0.3895955	0.7626817
9:123732000-123733000	0.4288805	0.7677095
9:123733000-123734000	0.4103963	0.5353838
9:123736000-123737000	0.4552633	0.8303799
9:124019000-124020000	0.9713213	0.5302002
9:124020000-124021000	0.8995141	0.5999564
10:3066000-3067000	0.5597303	0.3146165
10:57980000-57981000	0.3878843	0.2438369
11:3051000-3052000	0.5503324	0.2920643
11:3052000-3053000	0.4386169	0.2319910
11:3053000-3054000	0.3528213	0.2622936
11:3077000-3078000	0.3937139	0.3467826
11:3122000-3123000	0.3626074	0.3103051
11:5118000-5119000	0.3312702	0.4058122
11:20329000-20330000	0.3019849	0.3114479
11:105957000-105958000	0.3676806	0.3710582
12:55585000-55586000	0.3434316	0.2108226
12:105402000-105403000	0.4496502	0.3427045
12:113623000-113624000	0.3379417	0.3444453
12:113632000-113633000	0.3735360	0.3263238
12:113677000-113678000	0.3157709	0.2263731
12:113682000-113683000	0.3395115	0.2878012
12:113741000-113742000	0.4781619	0.2788916
12:114790000-114791000	0.3016608	0.3799773
12:115028000-115029000	0.3795644	0.4898224
12:115568000-115569000	0.4890586	0.3286808
12:115570000-115571000	0.4073457	0.2953227
12:115578000-115579000	0.5897693	0.2165716
12:115579000-115580000	0.3465052	0.2957641
12:115584000-115585000	0.4112218	0.2291257
12:115588000-115589000	0.3860118	0.2200045
12:115772000-115773000	0.4721239	0.2758600
12:115784000-115785000	0.3394347	0.3233559
12:115786000-115787000	0.4847051	0.2301149
13:9061000-9062000	0.5178549	0.4653214
13:45023000-45024000	0.5140563	0.4126249
13:48412000-48413000	0.7355344	0.3063239
13:48414000-48415000	0.6968362	0.2539953
13:48416000-48417000	0.8947746	0.3452178
13:48417000-48418000	0.5316108	0.2017636
13:48421000-48422000	0.8619118	0.2488569
13:100419000-100420000	0.3433883	0.2179959
13:100421000-100422000	0.3327397	0.2030761
13:100477000-100478000	0.3916319	0.3803050
13:100478000-100479000	0.3083588	0.4029012
13:120059000-120060000	0.4373825	0.3749182
13:120060000-120061000	0.6550080	0.4618200
13:120061000-120062000	0.4097712	0.5563000
13:120487000-120488000	0.3913565	0.3263754
14:15469000-15470000	0.3492126	0.4882167
14:18316000-18317000	0.3674816	0.3484549
14:25880000-25881000	0.3462215	0.3922358
14:122806000-122807000	0.4566111	0.2621270
15:21656000-21657000	0.4816046	0.3851019
15:83622000-83623000	0.3208542	0.3873723
16:3056000-3057000	0.3219073	0.3032661
16:3058000-3059000	0.3879135	0.2133975
16:3065000-3066000	0.3444538	0.3237271
16:3144000-3145000	0.3712380	0.3509514
16:3156000-3157000	0.3258096	0.3227946
16:3161000-3162000	0.3877128	0.2162309
16:3162000-3163000	0.3985442	0.2649061
16:17040000-17041000	0.4336138	0.2020359
16:57211000-57212000	0.7929593	0.3626401
17:3057000-3058000	0.4135265	0.2716128
17:3063000-3064000	0.4103832	0.2822227
17:3072000-3073000	0.6897618	0.3217266
17:3074000-3075000	0.3894668	0.3359431
17:3075000-3076000	0.3651646	0.2033785
17:3077000-3078000	0.4792289	0.3356187
17:3080000-3081000	0.9696840	0.2433070
17:3086000-3087000	0.3087418	0.2839404
17:13425000-13426000	0.3619291	0.2315976
17:13447000-13448000	0.3036552	0.2542737
17:13761000-13762000	0.4506390	0.2221712
17:13772000-13773000	1.1051892	0.2021514
17:13807000-13808000	0.3394806	0.2869085
18:73666000-73667000	0.5473445	0.3569516
18:82231000-82232000	0.3649288	0.2729084
19:6790000-6791000	0.8681514	0.3552265

plot(y$logMean,y$cv,pch=18,cex=0.5,xlab="log10(mean)",ylab="CV")
points(yy$logMean,yy$cv)

#text(yy$logMean,yy$cv+0.02,labels=rownames(yy),cex=0.8)

plot(y$logMean,y$cv,pch=18,cex=0.5,xlab="log10(mean)",ylab="CV",xlim=c(0,4.5),ylim=c(0,1))
points(yy$logMean,yy$cv)
text(yy$logMean,yy$cv+0.02,labels=rownames(yy),cex=0.8)

my_palette <- colorRampPalette(c("blue", "white", "red"))(n = 25)
zz <- x[which(rownames(x) %in% rownames(yy)),]
heatmap.2(as.matrix(zz),margin=c(8, 22),cexRow=0.65,trace="none",
  cexCol=0.8,col=my_palette,scale="row")

heatmap.2(cor(t(zz)),trace="none",scale="none",margins=c(12,12),
  cexRow=0.8, cexCol=0.8)

for (i in 1:19){
mychr=as.character(i)
regex=paste("^",mychr,":",sep="")
chr <- x[grep(regex,rownames(x)),]
mymax = max(chr)
plot(chr[,1], xaxt = "n", pch=19, col="gray",
  ylim=c(0,mymax),ylab="RPM of 1 kbp bins of chr",main=mychr)
axis(1, at=chr[,1], labels=rownames(chr), xlab="chr", las=1)
points( chr[,1], xaxt = "n", las=1, pch=19, col="gray"  )
points( chr[,2], xaxt = "n", las=1, pch=19, col="lightblue"  )
points( chr[,3], xaxt = "n", las=1, pch=19, col="lightgreen"  )
points( chr[,4], xaxt = "n", las=1, pch=19, col="pink" )
points( chr[,5], xaxt = "n", las=1, pch=19, col="orange" )
points( chr[,6], xaxt = "n", las=1, pch=19, col="black" )
grid()
}

lapply(1:19,function(i){
  mychr=as.character(i)
  regex=paste("^",mychr,":",sep="")
  chr <- x[grep(regex,rownames(x)),]
  mymedian <- median(rowMeans(chr))
  mymax <- max(rowMeans(chr))
  rat <- mymax / mymedian
  return(c(mymax,mymedian,rat))
})

## [[1]]
## [1] 17.0669535  0.3801317 44.8974730
## 
## [[2]]
## [1] 1.149764e+04 4.115003e-01 2.794078e+04
## 
## [[3]]
## [1]  8.8609429  0.3584881 24.7175388
## 
## [[4]]
## [1] 15.9841737  0.4034289 39.6207934
## 
## [[5]]
## [1]  5.4536493  0.4195186 12.9997792
## 
## [[6]]
## [1]  844.3785571    0.3884418 2173.7582043
## 
## [[7]]
## [1]  7.6563507  0.4386527 17.4542427
## 
## [[8]]
## [1] 3.4794687 0.4109625 8.4666325
## 
## [[9]]
## [1] 309.1596439   0.4363281 708.5485891
## 
## [[10]]
## [1]  6.8785538  0.3840956 17.9084435
## 
## [[11]]
## [1] 27.0898822  0.4665522 58.0639915
## 
## [[12]]
## [1] 23.2154726  0.3920841 59.2104479
## 
## [[13]]
## [1]  8.9645277  0.3945575 22.7204568
## 
## [[14]]
## [1]  43.1080695   0.3750425 114.9418139
## 
## [[15]]
## [1]  9.2323142  0.4004437 23.0552097
## 
## [[16]]
## [1]  6.2081080  0.3781252 16.4181284
## 
## [[17]]
## [1] 40.1686635  0.4182026 96.0507245
## 
## [[18]]
## [1] 3.5587554 0.3926506 9.0634152
## 
## [[19]]
## [1]  9.0138576  0.4310443 20.9116717

lapply(1:19,function(i){
  mychr=as.character(i)
  regex=paste("^",mychr,":",sep="")
  chr <- x[grep(regex,rownames(x)),]
  top <- head(chr[order(-rowMeans(chr)),])
  return(top)
})

## [[1]]
##                     SRX5884275.bam SRX5884276.bam SRX5884277.bam SRX5884278.bam
## 1:78585000-78586000      19.943879      18.924874      17.606571      15.315479
## 1:88183000-88184000       5.957263       3.996557       5.434127       3.668727
## 1:26725000-26726000       5.093891       3.643920       4.999397       3.610493
## 1:88151000-88152000       3.971508       3.408828       3.477841       4.658701
## 1:88141000-88142000       3.194474       5.524653       3.803889       3.057272
## 1:88177000-88178000       4.575868       4.114103       3.586524       2.649636
##                     SRX5884279.bam SRX5884280.bam
## 1:78585000-78586000      14.811623      15.799294
## 1:88183000-88184000       4.695327       3.007252
## 1:26725000-26726000       4.396534       3.545864
## 1:88151000-88152000       4.695327       4.892395
## 1:88141000-88142000       3.713577       3.860055
## 1:88177000-88178000       4.140425       3.545864
## 
## [[2]]
##                     SRX5884275.bam SRX5884276.bam SRX5884277.bam SRX5884278.bam
## 2:98497000-98498000     12560.7587    11800.07057    10518.94826     11780.6027
## 2:98496000-98497000       639.4129      648.50020      622.85963       613.6674
## 2:98495000-98496000       515.7781      504.50659      494.72292       605.2235
## 2:98492000-98493000       428.3185      387.19588      360.82603       367.3968
## 2:98493000-98494000       209.7129      206.41043      189.97708       176.4483
## 2:98494000-98495000        12.0872       12.10722       11.52035        10.8606
##                     SRX5884279.bam SRX5884280.bam
## 2:98497000-98498000   10585.273823    11740.17685
## 2:98496000-98497000     592.891778      622.72557
## 2:98495000-98496000     588.196451      600.41804
## 2:98492000-98493000     346.472467      382.23518
## 2:98493000-98494000     182.989709      186.58427
## 2:98494000-98495000       8.921122       10.45806
## 
## [[3]]
##                     SRX5884275.bam SRX5884276.bam SRX5884277.bam SRX5884278.bam
## 3:5925000-5926000         8.633714      11.049306       6.520952       8.880649
## 3:3041000-3042000         7.856680       6.700111       6.955683       7.861558
## 3:3005000-3006000         7.511331       7.052748       6.194905       5.910727
## 3:3010000-3011000         5.525577       6.229928       4.564667       5.124571
## 3:3039000-3040000         3.108137       5.054470       6.194905       4.454883
## 3:56483000-56484000       2.935463       4.701832       2.934429       2.853454
##                     SRX5884279.bam SRX5884280.bam
## 3:5925000-5926000         7.982056      10.098980
## 3:3041000-3042000         7.171045       7.361035
## 3:3005000-3006000         7.085676       6.149157
## 3:3010000-3011000         6.231980       6.328694
## 3:3039000-3040000         4.055055       4.084476
## 3:56483000-56484000       3.628207       3.994708
## 
## [[4]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 4:118405000-118406000      15.540685      18.337145      20.432317
## 4:3083000-3084000          12.432548      15.751138      16.519746
## 4:3081000-3082000           8.979062      11.049306      11.302984
## 4:3050000-3051000           9.497085       8.580844      11.846397
## 4:156423000-156424000       6.647960       7.052748       7.390413
## 4:3082000-3083000           7.079645       6.817657       7.716460
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 4:118405000-118406000      15.082544      14.214036      12.298314
## 4:3083000-3084000          12.694960      15.281156      10.009212
## 4:3081000-3082000           7.250103       8.835752       6.283810
## 4:3050000-3051000           7.832441       7.768632       7.136613
## 4:156423000-156424000       7.162753       7.000306       7.271266
## 4:3082000-3083000           7.715973       6.402719       6.014504
## 
## [[5]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 5:146197000-146198000       6.388948       7.875569       5.325444
## 5:115060000-115061000       3.798834       3.761466       4.564667
## 5:146198000-146199000       4.230520       2.938645       2.173651
## 5:26273000-26274000         3.021800       2.468462       3.151794
## 5:26215000-26216000         2.417440       1.998279       2.173651
## 5:26212000-26213000         2.503777       2.115824       1.195508
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 5:146197000-146198000       4.891636       3.841631       4.398667
## 5:115060000-115061000       2.911688       4.097740       3.994708
## 5:146198000-146199000       3.115506       2.603772       3.231674
## 5:26273000-26274000         3.115506       2.603772       3.860055
## 5:26215000-26216000         2.358467       1.622022       2.648177
## 5:26212000-26213000         2.620519       2.603772       1.885143
## 
## [[6]]
##                       SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 6:103626000-103627000     880.207133    868.0757587     855.874998
## 6:29748000-29749000        12.173537      7.5229314      10.107476
## 6:87434000-87435000         1.381394      3.0561909       3.912571
## 6:121287000-121288000       1.467731      0.7052748       1.847603
## 6:115999000-116000000       2.158428      0.9403664       2.608381
## 6:47630000-47631000         1.381394      2.9386451       1.738921
##                       SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 6:103626000-103627000     826.657366    804.7364071     830.719680
## 6:29748000-29749000         7.483038      7.8540020       7.091728
## 6:87434000-87435000         2.387584      3.0733051       2.917483
## 6:121287000-121288000       3.377558      2.3903484       2.244218
## 6:115999000-116000000       1.688779      1.4939678       1.840259
## 6:47630000-47631000         1.252026      0.9817502       1.346531
## 
## [[7]]
##                     SRX5884275.bam SRX5884276.bam SRX5884277.bam SRX5884278.bam
## 7:11744000-11745000       8.115691       9.521210       7.716460       7.395688
## 7:59419000-59420000       3.971508       1.645641       4.999397       2.562286
## 7:63723000-63724000       1.640406       2.703553       3.912571       2.824337
## 7:63730000-63731000       1.726743       2.938645       2.934429       1.368493
## 7:63728000-63729000       1.985754       1.645641       2.717063       2.474935
## 7:38099000-38100000       1.554069       1.645641       2.391016       2.649636
##                     SRX5884279.bam SRX5884280.bam
## 7:11744000-11745000       6.231980       6.957075
## 7:59419000-59420000       3.329414       2.782830
## 7:63723000-63724000       2.945251       2.782830
## 7:63730000-63731000       2.518403       2.244218
## 7:63728000-63729000       1.963500       1.885143
## 7:38099000-38100000       2.091555       1.436299
## 
## [[8]]
##                     SRX5884275.bam SRX5884276.bam SRX5884277.bam SRX5884278.bam
## 8:14356000-14357000       3.798834       4.936924       3.803889       2.795221
## 8:74345000-74346000       3.194474       1.763187       4.021254       2.125532
## 8:21437000-21438000       2.072091       1.175458       2.825746       2.591402
## 8:21054000-21055000       1.208720       3.291282       3.369159       1.455844
## 8:75704000-75705000       1.899417       2.350916       2.282333       1.601428
## 8:94653000-94654000       1.036046       3.761466       2.173651       1.455844
##                     SRX5884279.bam SRX5884280.bam
## 8:14356000-14357000       3.073305       2.468640
## 8:74345000-74346000       3.073305       1.840259
## 8:21437000-21438000       2.134240       2.872599
## 8:21054000-21055000       1.878131       2.199333
## 8:75704000-75705000       1.707392       1.974912
## 8:94653000-94654000       1.323229       1.795374
## 
## [[9]]
##                     SRX5884275.bam SRX5884276.bam SRX5884277.bam SRX5884278.bam
## 9:35216000-35217000      329.98055      311.96656      288.33478      316.09286
## 9:3000000-3001000        196.76234      188.77856      172.15314      200.26591
## 9:3001000-3002000        120.87199      127.41965      107.48703      121.09711
## 9:3002000-3003000        123.54845      114.95980      101.83554      104.47137
## 9:3024000-3025000         92.29440       91.09800       84.55502       91.42701
## 9:3006000-3007000         64.75285       69.82221       58.03648       73.54924
##                     SRX5884279.bam SRX5884280.bam
## 9:35216000-35217000      294.48239      314.10073
## 9:3000000-3001000        176.33088      215.93864
## 9:3001000-3002000        118.19419      127.96530
## 9:3002000-3003000        100.73611      105.34359
## 9:3024000-3025000         84.55858       94.66111
## 9:3006000-3007000         67.10049       65.39651
## 
## [[10]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 10:128277000-128278000       7.943017       5.877290       6.412270
## 10:3062000-3063000           4.575868       7.287840       6.194905
## 10:57982000-57983000         4.403194       4.701832       3.586524
## 10:57981000-57982000         4.575868       4.114103       5.108079
## 10:3063000-3064000           4.144183       3.996557       3.695206
## 10:3066000-3067000           3.367148       2.350916       5.108079
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 10:128277000-128278000       7.686857       7.427154       5.924735
## 10:3062000-3063000           5.270155       7.469839       6.957075
## 10:57982000-57983000         4.542233       5.079490       4.174245
## 10:57981000-57982000         3.581376       4.609958       3.994708
## 10:3063000-3064000           3.028156       3.286729       4.398667
## 10:3066000-3067000           2.329350       4.396534       4.219130
## 
## [[11]]
##                    SRX5884275.bam SRX5884276.bam SRX5884277.bam SRX5884278.bam
## 11:3143000-3144000       25.64213       29.38645       27.49668       26.20519
## 11:3135000-3136000       17.09475       19.15997       18.47603       16.30545
## 11:3146000-3147000       15.88603       17.63187       17.28052       17.79041
## 11:3139000-3140000       19.25318       14.92832       16.95448       15.92693
## 11:3134000-3135000       15.62702       14.45813       18.25867       14.23815
## 11:3144000-3145000       17.52644       17.51432       12.82454       14.70402
##                    SRX5884279.bam SRX5884280.bam
## 11:3143000-3144000       27.14753       26.66131
## 11:3135000-3136000       18.31178       16.96629
## 11:3146000-3147000       15.83606       17.41513
## 11:3139000-3140000       14.59820       14.85672
## 11:3134000-3135000       17.92761       14.22834
## 11:3144000-3145000       17.24466       14.72207
## 
## [[12]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 12:3159000-3160000          27.368873      27.153081      20.323635
## 12:67106000-67107000        14.936325      19.982787      15.758968
## 12:74851000-74852000         7.079645       6.582565       8.368556
## 12:3160000-3161000           6.043600       6.465019       4.782032
## 12:115580000-115581000       4.662206       4.936924       4.564667
## 12:115581000-115582000       5.352903       4.936924       4.021254
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 12:3159000-3160000          22.157946      20.744810      21.544491
## 12:67106000-67107000        16.305453      18.397146      17.011171
## 12:74851000-74852000         6.667766       5.762447       7.450803
## 12:3160000-3161000           4.309298       4.866066       4.488436
## 12:115580000-115581000       4.775168       4.396534       4.578204
## 12:115581000-115582000       4.251065       4.012371       3.949823
## 
## [[13]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 13:48422000-48423000       9.151737       9.403664       9.564063
## 13:48416000-48417000       7.079645      12.342309       9.672746
## 13:48411000-48412000       7.079645       8.345752       6.629635
## 13:48415000-48416000       8.720051       7.875569       9.455381
## 13:48421000-48422000      10.792142       7.052748       5.868857
## 13:48407000-48408000       6.302611       8.110660       6.955683
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 13:48422000-48423000       9.288285       9.646763       6.732654
## 13:48416000-48417000       5.619558       7.213730       5.161701
## 13:48411000-48412000       7.453922       7.256415       9.201293
## 13:48415000-48416000       6.842467       7.085676       5.475892
## 13:48421000-48422000       6.231013       7.384469       6.328694
## 13:48407000-48408000       7.715973       7.854002       6.642885
## 
## [[14]]
##                        SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 14:3052000-3053000          45.845021      46.900776      43.690381
## 14:3051000-3052000          48.521472      43.727039      41.951460
## 14:3050000-3051000          35.398227      32.560188      36.734698
## 14:3053000-3054000          35.657238      33.030371      30.539794
## 14:122806000-122807000       2.762788       1.880733       3.912571
## 14:18316000-18317000         1.985754       1.293004       1.738921
##                        SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 14:3052000-3053000          38.521633      42.172576      41.518030
## 14:3051000-3052000          37.560776      36.367444      39.184044
## 14:3050000-3051000          31.242413      28.470757      30.117404
## 14:3053000-3054000          29.320699      30.391573      31.239512
## 14:122806000-122807000       2.824337       3.500153       2.289102
## 14:18316000-18317000         3.464909       2.987936       2.513524
## 
## [[15]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 15:74958000-74959000       9.410748      10.461577      11.411667
## 15:60013000-60014000       7.770343      10.931760       8.694603
## 15:21656000-21657000       4.403194       4.231649       1.304190
## 15:78637000-78638000       1.726743       1.645641       2.064968
## 15:83622000-83623000       1.122383       2.938645       3.043111
## 15:91670000-91671000       1.295057       1.410550       1.521556
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 15:74958000-74959000       7.715973       8.494274       7.899647
## 15:60013000-60014000      10.190908       8.921122       8.303606
## 15:21656000-21657000       2.416701       2.689142       3.141905
## 15:78637000-78638000       2.736987       2.433033       2.109565
## 15:83622000-83623000       1.979948       2.219609       1.256762
## 15:91670000-91671000       1.193792       2.091555       2.109565
## 
## [[16]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 16:57211000-57212000       4.834880      10.226485       6.738317
## 16:91331000-91332000       4.921217       5.407107       4.673349
## 16:3050000-3051000         4.144183       4.819378       4.347302
## 16:3054000-3055000         4.403194       3.879012       3.912571
## 16:3052000-3053000         4.403194       3.643920       3.695206
## 16:3051000-3052000         3.626160       4.349195       2.825746
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 16:57211000-57212000       6.347480       5.420969       3.680517
## 16:91331000-91332000       4.280181       4.140425       5.475892
## 16:3050000-3051000         3.756078       4.695327       3.366327
## 16:3054000-3055000         3.377558       4.609958       3.949823
## 16:3052000-3053000         3.814311       3.030620       3.456095
## 16:3051000-3052000         2.853454       4.055055       3.725402
## 
## [[17]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 17:40154000-40155000       40.66479       45.25513       43.58170
## 17:40155000-40156000       39.36974       46.19550       39.23440
## 17:40156000-40157000       36.26160       43.49195       35.64787
## 17:13525000-13526000       32.37643       28.21099       33.58290
## 17:40158000-40159000       27.19620       29.38645       32.49608
## 17:13773000-13774000       26.85085       32.91282       34.77841
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 17:40154000-40155000       36.10493       38.33094       37.07448
## 17:40155000-40156000       35.31878       33.12340       31.59859
## 17:40156000-40157000       29.32070       29.87936       30.20717
## 17:13525000-13526000       23.17704       29.62325       27.06527
## 17:40158000-40159000       27.10782       29.58056       26.66131
## 17:13773000-13774000       23.90496       27.23290       22.53195
## 
## [[18]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 18:82205000-82206000       3.971508      3.0561909       3.369159
## 18:73666000-73667000       3.885171      3.6439199       5.760175
## 18:82231000-82232000       2.935463      1.4105496       1.956286
## 18:82211000-82212000       2.244766      1.6456412       2.173651
## 18:3118000-3119000         1.295057      1.0579122       2.064968
## 18:3115000-3116000         2.072091      0.7052748       1.521556
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 18:82205000-82206000       3.581376       4.097740       3.276558
## 18:73666000-73667000       2.940805       2.774512       2.154449
## 18:82231000-82232000       2.329350       3.115990       2.154449
## 18:82211000-82212000       1.921714       1.152489       2.603293
## 18:3118000-3119000         1.921714       1.835446       1.885143
## 18:3115000-3116000         2.154649       1.323229       1.885143
## 
## [[19]]
##                      SRX5884275.bam SRX5884276.bam SRX5884277.bam
## 19:58101000-58102000      11.828188       8.345752       9.129333
## 19:6790000-6791000        11.828188       7.522931       8.585921
## 19:10650000-10651000       2.849126       2.115824       2.391016
## 19:6739000-6740000         1.726743       2.586008       1.738921
## 19:3311000-3312000         2.072091       2.233370       1.738921
## 19:8570000-8571000         2.676451       1.410550       1.956286
##                      SRX5884278.bam SRX5884279.bam SRX5884280.bam
## 19:58101000-58102000      7.6286228      9.4760241       7.675225
## 19:6790000-6791000        5.0663373      6.5734582       4.712857
## 19:10650000-10651000      1.6596622      0.8110111       1.570952
## 19:6739000-6740000        1.6887791      1.1098046       1.705606
## 19:3311000-3312000        1.4849609      0.8110111       1.122109
## 19:8570000-8571000        0.8735064      1.1098046       1.346531

Session information

sessionInfo()

## R version 4.1.1 (2021-08-10)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.3 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
## 
## 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  stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
## [1] kableExtra_1.3.4 dplyr_1.0.7      gplots_3.1.1     quantreg_5.86   
## [5] SparseM_1.81     cobs_1.3-4      
## 
## loaded via a namespace (and not attached):
##  [1] gtools_3.9.2       tidyselect_1.1.1   xfun_0.25          bslib_0.2.5.1     
##  [5] purrr_0.3.4        splines_4.1.1      lattice_0.20-45    colorspace_2.0-2  
##  [9] vctrs_0.3.8        generics_0.1.0     htmltools_0.5.1.1  viridisLite_0.4.0 
## [13] yaml_2.2.1         utf8_1.2.2         rlang_0.4.11       jquerylib_0.1.4   
## [17] pillar_1.6.2       glue_1.4.2         DBI_1.1.1          matrixStats_0.60.0
## [21] lifecycle_1.0.0    stringr_1.4.0      MatrixModels_0.5-0 munsell_0.5.0     
## [25] rvest_1.0.1        caTools_1.18.2     evaluate_0.14      knitr_1.33        
## [29] fansi_0.5.0        highr_0.9          Rcpp_1.0.7         KernSmooth_2.23-20
## [33] conquer_1.0.2      scales_1.1.1       jsonlite_1.7.2     webshot_0.5.2     
## [37] systemfonts_1.0.2  digest_0.6.27      stringi_1.7.3      grid_4.1.1        
## [41] tools_4.1.1        bitops_1.0-7       sass_0.4.0         magrittr_2.0.1    
## [45] tibble_3.1.3       crayon_1.4.1       pkgconfig_2.0.3    ellipsis_0.3.2    
## [49] Matrix_1.3-4       xml2_1.3.2         assertthat_0.2.1   rmarkdown_2.10    
## [53] svglite_2.0.0      httr_1.4.2         rstudioapi_0.13    R6_2.5.0          
## [57] compiler_4.1.1