kobas.plage {KOBAS} R Documentation

PLAGE pathway level analysis (KOBAS SNBEA)

Description

<br /> Score each gene set of the expression matrix with the PLAGE method (the first<br /> right singular vector of the row standardized gene set submatrix), then compare<br /> the activity scores between the two phenotype groups.

Usage

kobas.plage(expr, cls, gmt,
    min.size = 5,
    max.size = 500,
    fdr = "BH",
    data.type = "rseq",
    normalize = TRUE);

Arguments

expr

the expression matrix (matrix object, dataframe or expression matrix file path).

cls

the phenotype class labels, same as the cls parameter of kobas.gsea.

gmt

the gene set collection: a Background model or a GMT file path.

min.size

the minimum number of the mapped members of a gene set, default 5. [as integer]

max.size

the maximum number of the mapped members of a gene set, default 500. [as integer]

fdr

the multiple testing correction method, default BH. [as string]

data.type

the data type of the expression matrix: rseq (RNA-seq read counts, default) or ma (microarray data). [as string]

normalize

performs the data normalization before the analysis? Default TRUE: the RNA-seq data will be transformed by the log2 CPM with the prior count and the microarray data will be quantile normalized. [as boolean]

env

the R# runtime environment. [as Environment]

Details

The differential analysis uses the classic Welch two sample t-test instead of the limma moderated t-test because there is no moderated t implementation in the GCModeller core library, so the p-values are slightly more conservative than the limma result.

Authors

gseakit

Value

a dataframe with the gene set id as the row names and the columns: name, description, size, statistic, pvalue, p_adjust and genes.

clr value class

Examples

[Package KOBAS version 1.0.0.0 Index]