Last updated: 2018-06-06

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  • ✖ R Markdown file: uncommitted changes The R Markdown file has unstaged changes. To know which version of the R Markdown file created these results, you’ll want to first commit it to the Git repo. If you’re still working on the analysis, you can ignore this warning. When you’re finished, you can run wflow_publish to commit the R Markdown file and build the HTML.

  • ✔ Environment: empty

    Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

  • ✔ Seed: set.seed(1)

    The command set.seed(1) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

  • ✔ Session information: recorded

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  • ✔ Repository version: dae0caf

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Ignored files:
    Ignored:    .sos/
    Ignored:    data/.sos/
    Ignored:    output/MatrixEQTLSumStats.Portable.Z.coved.K3.P3.lite.single.expanded.V1.loglik.rds
    Ignored:    workflows/.ipynb_checkpoints/
    Ignored:    workflows/.sos/

Untracked files:
    Untracked:  analysis/files.txt
    Untracked:  fastqtl_to_mash_output/
    Untracked:  gtex6_workflow_output/

Unstaged changes:
    Modified:   analysis/Tspecific.Rmd
    Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
Expand here to see past versions:
    File Version Author Date Message
    Rmd dae0caf Peter Carbonetto 2018-06-06 Renamed Tspecific analysis.
    html afc401f Peter Carbonetto 2017-09-20 Moved doc to docs.
    Rmd e1e48df Peter Carbonetto 2017-09-20 Reorganized many of the files.

Add text here.

Set up environment

First, we load some functions defined for mash analyses.

source("../code/normfuncs.R")

Add text here.

thresh <- 0.05

Load data and mash results

Load some GTEx summary statistics, as well as some of the results generated from the mash analysis of the GTEx data.

out <- readRDS("../data/MatrixEQTLSumStats.Portable.Z.rds")
maxb           <- out$test.b
maxz           <- out$test.z
standard.error <- out$test.s
out <- readRDS(paste("../output/MatrixEQTLSumStats.Portable.Z.coved.K3.P3",
                     "lite.single.expanded.V1.posterior.rds",sep = "."))
pm.mash      <- out$posterior.means
lfsr.mash    <- out$lfsr
pm.mash.beta <- pm.mash * standard.error
nsig                <- rowSums(lfsr.mash<thresh)
pm.mash.beta.norm   <- het.norm(effectsize = pm.mash.beta)
pm.mash.beta.norm   <- pm.mash.beta.norm[(nsig>0),]
lfsr.mash           <- as.matrix(lfsr.mash[nsig>0,])
colnames(lfsr.mash) <- colnames(maxz)
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,]
col = as.character(color.gtex[,2])
a=which(rowSums(pm.mash.beta.norm>0.5)==1)
lfsr.fold=as.matrix(lfsr.mash[a,])
pm <- as.matrix(pm.mash.beta.norm[a,])
tspec=NULL
for(i in 1:ncol(pm)){
  tspec[i]=sum(pm[,i]>0.5)
}
tspec           <- as.matrix(tspec)
rownames(tspec) <- colnames(maxz)
barplot(as.numeric(t(tspec)),las = 2,cex.names = 0.3,col = col,
        names = colnames(lfsr.fold))

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     
# 
# 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    backports_1.1.2     
#  [7] git2r_0.21.0         magrittr_1.5         evaluate_0.10.1     
# [10] stringi_1.1.7        whisker_0.3-2        R.oo_1.21.0         
# [13] R.utils_2.6.0        rmarkdown_1.9        tools_3.4.3         
# [16] stringr_1.3.0        yaml_2.1.18          compiler_3.4.3      
# [19] htmltools_0.3.6      knitr_1.20

This reproducible R Markdown analysis was created with workflowr 1.0.1.9000