Last updated: 2018-05-18

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Expand here to see past versions:
    File Version Author Date Message
    Rmd 37ef62c Peter Carbonetto 2018-05-18 wflow_publish(“Fig.Uk*.Rmd“)
    html 02aae6b Peter Carbonetto 2018-05-18 Revised Fig.Uk8.Rmd for analysis of testis-specific effects components.
    Rmd e1016bb Peter Carbonetto 2018-05-18 wflow_publish(c(“Fig.Uk8.Rmd”, “Fig.Uk3.Rmd”, “Fig.Uk2.Rmd”))
    Rmd 80f285f Gao Wang 2017-09-20 Update figures
    html 80f285f Gao Wang 2017-09-20 Update figures

Here we plot the correlation matrix for the eighth covariance component, which captures testis-specific effects.

Set up environment

First, we load a couple plotting packages used in the code chunks below.

library(lattice)
library(colorRamps)

Load data and MASH results

In the next code chunk, we load some GTEx summary statistics, as well as some of the results generated from the MASH analysis of the GTEx data.

covmat <- readRDS(paste("../output/MatrixEQTLSumStats.Portable.Z.coved.K3.P3",
                        "lite.single.expanded.rds",sep = "."))
pis    <- readRDS(paste("../output/MatrixEQTLSumStats.Portable.Z.coved.K3.P3",
                        "lite.single.expanded.V1.pihat.rds",sep = "."))$pihat
z.stat <- readRDS("../data/MatrixEQTLSumStats.Portable.Z.rds")$test.z
pi.mat <- matrix(pis[-length(pis)],ncol = 54,nrow = 22,byrow = TRUE)
names  <- colnames(z.stat)

Next, we load the tissue indices:

h <- read.table("../output/uk8rowIndices.txt")[,1]

For the plots of the eigenvectors, we load the colours that are conventionally used to represent the tissues in plots.

missing.tissues <- c(7,8,19,20,24,25,31,34,37)
color.gtex      <- read.table("../data/GTExColors.txt",sep = '\t',
                              comment.char = '')[-missing.tissues,]

Compute the correlations from the \(k=8\) covariance matrix.

k           <- 8
x           <- cov2cor(covmat[[k]])
x[x<0]      <- 0
colnames(x) <- names
rownames(x) <- names

Generate heatmap of Uk8 covariance matrix

Now we produce the heatmap showing the full covariance matrix.

clrs <- colorRampPalette(rev(c("#D73027","#FC8D59","#FEE090","#FFFFBF",
                               "#E0F3F8","#91BFDB","#4575B4")))(64)
lat=x[rev(h),rev(h)]
lat[lower.tri(lat)] <- NA
n=nrow(lat)
print(levelplot(lat[n:1,],col.regions = clrs,xlab = "",ylab = "",
      colorkey = TRUE))

Expand here to see past versions of heatmapuk8final-1.png:
Version Author Date
02aae6b Peter Carbonetto 2018-05-18

Plot eigenvector capturing the predominant pattern

The top eigenvector captures the predominant pattern in the Uk8 covariance matrix.

col = as.character(color.gtex[,2])
k=8
g=1
v=svd(covmat[[k]])$v[h,]
rownames(v)=colnames(v)=names[h]
par(mar=c(8,4.1,4.1,2.1))
barplot(v[,g]/v[which.max(abs(v[,g])),g],las=2,
        main=paste("Eigenvector",g,"of Uk",k),
        cex.names = 0.5,col=col[h],names=names[h])

Expand here to see past versions of plot-eigenvectors-1.png:
Version Author Date
02aae6b Peter Carbonetto 2018-05-18

Session information

sessionInfo()
R version 3.4.3 (2017-11-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.4

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

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] colorRamps_2.3  lattice_0.20-35

loaded via a namespace (and not attached):
 [1] workflowr_1.0.1.9000 Rcpp_0.12.16         digest_0.6.15       
 [4] rprojroot_1.3-2      R.methodsS3_1.7.1    grid_3.4.3          
 [7] backports_1.1.2      git2r_0.21.0         magrittr_1.5        
[10] evaluate_0.10.1      stringi_1.1.7        whisker_0.3-2       
[13] R.oo_1.21.0          R.utils_2.6.0        rmarkdown_1.9       
[16] tools_3.4.3          stringr_1.3.0        yaml_2.1.18         
[19] compiler_3.4.3       htmltools_0.3.6      knitr_1.20

This reproducible R Markdown analysis was created with workflowr 1.0.1.9000