View source: R/aggregateGSVAscores.R
aggregateGSVAscores | R Documentation |
Replaces GSVA results from paired up- and down- gene sets with the difference of the up-regulated genes and down-regulated genes
aggregateGSVAscores(aggList, K2res)
aggList |
A list where each item is a vector of 3 items: the new name, the name of the 'up' gene set, and the name of the 'down' gene set. |
K2res |
An object of class K2. The output of runDGEmods(). |
An object of class K2.
reed_2020K2Taxonomer \insertRefgsvaK2Taxonomer
## Read in ExpressionSet object
library(Biobase)
data(sample.ExpressionSet)
## Pre-process and create K2 object
K2res <- K2preproc(sample.ExpressionSet)
## Run K2 Taxonomer algorithm
K2res <- K2tax(K2res,
stabThresh=0.5)
## Run differential analysis on each partition
K2res <- runDGEmods(K2res)
## Create dummy set of gene sets
DGEtable <- getDGETable(K2res)
genes <- unique(DGEtable$gene)
genesetsMadeUp <- list(
GS1=genes[1:50],
GS2=genes[51:100],
GS3=genes[101:150])
## Run gene set hyperenrichment
K2res <- runGSEmods(K2res,
genesets=genesetsMadeUp,
qthresh=0.1)
## Run GSVA on genesets
K2res <- runGSVAmods(K2res,
ssGSEAalg='gsva',
ssGSEAcores=1,
verbose=FALSE)
## Aggregate paired gene sets
aggList <- list(c('GS12', 'GS1', 'GS2'))
K2res <- aggregateGSVAscores(aggList, K2res)
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