I am trying to use PEER in R (on conda) to identify hidden confounders in the raw counts of my RNA-seq experiment. I am following their tutorial ( https://github.com/PMBio/peer/wiki/Tutorial ), but without much luck, and there's not much help available unfortunately. Anyone used this tool before and could advise?
I have installed R-PEER on Conda, but am having issues with following with the PEER pipeline, to identify 10 hidden confounders in my expression data. I was wondering if anyone could advise? I couldn't find much help online.
> $ source activate r-peer (r-peer) > $ R >library(peer) > expr <- read.table("~/raw_counts.tsv", header=TRUE) > dim(expr) > 14211 538 # 14211 row-genes, 538 col-samples > expr <- t(expr) # transpose > model = PEER() > PEER_setPhenoMean(model,as.matrix(expr)) >  NA # in the tutorial, it says this should be "NULL" > PEER_setNk(model,10) # so PEER identifies 10 hidden confounders >PEER_getNk(model)  10 > PEER_update(model) > iteration 0/1000 > iteration 1/1000 >Converged (bound) after 1 iterations NULL ###### why isn't it iterating? > > > sessionInfo() R version 3.4.1 (2017-06-30) Platform: > x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 18.04.1 LTS > > Matrix products: default BLAS: > /home/rodrigo/miniconda2/envs/r-peer/lib/R/lib/libRblas.so LAPACK: > /home/rodrigo/miniconda2/envs/r-peer/lib/R/lib/libRlapack.so > > locale:  LC_CTYPE=C.UTF-8 LC_NUMERIC=C > LC_TIME=C.UTF-8  LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 > LC_MESSAGES=C.UTF-8  LC_PAPER=C.UTF-8 LC_NAME=C > LC_ADDRESS=C  LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 > LC_IDENTIFICATION=C > > attached base packages:  stats graphics grDevices utils > datasets methods base > > other attached packages:  peer_1.0 > > loaded via a namespace (and not attached):  compiler_3.4.1