pairwise plot of flash result of flash Z-score and loading of flash on logcpm of count data

pairwise loading plot of Z-score

load("../data/GTExdata/bflashvarcol.rds")
dat = read.table('../data/GTExColors.txt', sep = '\t', comment.char = '')
colordata = dat[c(1:6,9:18,21:23,26:30,32,33,35,36,38:53),1:2]

i = 1
j = 3
plot(b_flash$l[,i],b_flash$l[,j],col = as.vector(colordata[,2]),pch = 16)
text(b_flash$l[,i],b_flash$l[,j], labels=colordata[,1], cex= 0.7)

i = 1
j = 3
plot(b_flash$f[,i],b_flash$f[,j],col = "grey",pch = 16)

plot(as.vector(b_flash$l[,i] %*% t(b_flash$f[,i])),
     as.vector(b_flash$l[,j] %*% t(b_flash$f[,j])),col = "grey",pch = 16)

logcpm of count

here I use - 2 brain tissues - testis + pituitary - 2 skin - Mammary+ adipose - 2 heart - uterus + Ovary

for each tissue, we random pick 50 smaples.

bfl = readRDS("../data/GTExdata/logcpm/sixpairssubsample/bflash_varcol.rds")

I run flash with K=60 and it provide 60 factors in greedy algorithm, which mean it didn’t stop. I run backfitting procedure with 6 iteration due to the time limit, it still provide 60 factors.

I am not sure the factor are useful a

color_six = c(rep("#eeee00",100),rep("#aaaaaa",50),rep("#aaff99",50),
              rep("#0000ff",50),rep("#7777ff",50),
              rep("#ffaa00",50),rep("#33cccc",50),
              rep("#9900ff",50),rep("#660099",50),
              rep("#ff66ff",50),rep("#ffaaff",50))

par(mfrow = c(3,3),mar = c(5,4,4,2)-1.8)
for(i in 1:60){
  barplot(bfl$l[,i],col = color_six,border = color_six)
}

gsvd = readRDS("../data/GTExdata/logcpm/sixpairssubsample/svd60.rds")
par(mfrow = c(3,3),mar = c(5,4,4,2)-1.8)
for(i in 1:60){
  barplot(gsvd$u[,i],col = color_six,border = color_six)
}

Session information

sessionInfo()

R version 3.3.0 (2016-05-03)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X 10.12.4 (unknown)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] workflowr_0.4.0 rmarkdown_1.3  

loaded via a namespace (and not attached):
 [1] backports_1.0.5 magrittr_1.5    rprojroot_1.2   htmltools_0.3.5
 [5] tools_3.3.0     yaml_2.1.14     Rcpp_0.12.10    stringi_1.1.2  
 [9] knitr_1.15.1    git2r_0.18.0    stringr_1.2.0   digest_0.6.12  
[13] evaluate_0.10