probeset2gene: Transform probe set to gene level data

In tgirke/longevityTools: Analysis tools for longevity research

Description

Function translates a binary DEG matrix from the probe level (row.names are Affy IDs) to the gene level (row.names are gene IDs). Genes represented by several probe sets (rows) will be collapsed based on a chosen summary rule.

Usage

probeset2gene(degMA, myAnnot, geneIDtype = "ENTREZID", summary_rule = 1L)

Arguments

degMA	Binary DEG matrix where row.names are Affy IDs.
myAnnot	Annotation data.frame containing Affy to gene ID mappings.
geneIDtype	Single character value referencing the gene ID column in myAnnot that should be used.
summary_rule	The following summary rules are supported: summary_rule=1L will consider a gene as a DEG for a specific treatment if at least one of several probe sets supports this assignment, while summary_rule=2L requires support from at least 2 probe sets.

Value

Binary matrix where row.names are gene IDs and col.names treatments; 1s indicate DEGs.

Author(s)

Thomas Girke

Examples

## Not run: 
## Import input data
myAnnot <- readRDS("./results/myAnnot.rds")
degMA <- readRDS("./results/degMA.rds") # Faster than read.delim()

## Transform probe set to gene level data
degMAgene <- probeset2gene(degMA, myAnnot, geneIDtype="ENTREZID", summary_rule=1L)
saveRDS(degMAgene, "./results/degMAgene.rds")


## End(Not run)

tgirke/longevityTools documentation built on May 31, 2019, 9:07 a.m.