inst/misc/makeTRN-proximalonly-demo.R

In TReNA: Fit transcriptional regulatory networks using gene expression, priors, machine learning

library(TReNA)

# 0. set options
genome.db.uri = "postgres://whovian/hg38"
project.db.uri = "postgres://whovian/lymphoblast"
out = "/proj/price1/sament/lymphoblast_trn/hg38.lymphoblast"
cores = 5
method = "lasso"
print(load(system.file(package="TReNA","/extdata/GSE37772.expr.RData")))
expr = expr2
rm( expr2 )

# 1, get counts of binding sites for each TF proximal to each gene (by default +/- 10kb from the TSS)

promoter_counts = getTfbsCountsInPromoters( 
   genome.db.uri=genome.db.uri , project.db.uri=project.db.uri , 
   size.upstream = 10000 , size.downstream = 10000 , # define the size of the window around the TSS
   cores = cores ) # specify the number of cores for parallelization

save( promoter_counts , file = paste( out , ".promoter_tfbs_counts.gene_ids.RData" , sep="" ))
  
# 2. build TRN model by integrating TFBS counts with expression data

trn = makeTrnFromPromoterCountsAndExpression( counts = promoter_counts , expr = expr , 
   method = method , cores = cores )

save( trn , file = paste( out , ".trn.RData" , sep = "" ))