nsdiffToFGSEA: Run gene set enrichment analysis using DE results.

In calebclass/NanoTube: An Easy Pipeline for NanoString nCounter Data Analysis

Run gene set enrichment analysis using DE results.

Description

Use the fgsea library to run gene set enrichment analysis from the NanoStringDiff analysis results. Genes will be ranked by their log2 fold changes.

Usage

nsdiffToFGSEA(deResults, gene.sets, sourceDB = NULL, min.set = 1)

Arguments

deResults	Result from NanoStringDiff::glm.LRT.
gene.sets	Gene set file name, in .rds (list), .gmt, or .tab format; or a list object containing the gene sets. Gene names must be in the same form as in the ranked.list.
sourceDB	Source database to include, only if using a .tab-format geneset.file from CPDB.
min.set	Number of genes required to conduct analysis on a given gene set (default = 1). If fewer than this number of genes from limmaResults are included in a gene set, that gene set will be skipped for this analysis.

Value

A list containing data frames with the fgsea results.

Examples

 
example_data <- system.file("extdata", "GSE117751_RAW", package = "NanoTube")
sample_data <- system.file("extdata", "GSE117751_sample_data.csv", 
                           package = "NanoTube")

datNoNorm <- processNanostringData(nsFiles = example_data,
                                   sampleTab = sample_data, 
                                   groupCol = "Sample_Diagnosis",
                                   normalization = "none")

# Convert to NanoString Set, retaining 2 samples per group for this example
# (will run faster, but still pretty slow)
nsDiffSet <- makeNanoStringSetFromEset(datNoNorm[,c(1,2,15,16,29,30)])

# Run NanoStringDiff analysis
nsDiffSet <- NanoStringDiff::estNormalizationFactors(nsDiffSet)
result <- NanoStringDiff::glm.LRT(nsDiffSet, 
                                  design.full = as.matrix(pData(nsDiffSet)),
                                  contrast = c(1, -1, 0)) 
                                  #contrast: Autoimmune retinopathy vs. None

# FGSEA with example pathways, only for pathways with at least 5 genes
# analyzed in NanoString experiment
data("ExamplePathways")
fgseaResult <- nsdiffToFGSEA(result, gene.sets = ExamplePathways,
                             min.set = 5)

calebclass/NanoTube documentation built on Nov. 21, 2023, 12:31 p.m.