uvPat: Uni-Variate Gene Set Analysis Pattern Classification.

In dmontaner/mdgsa: Multi Dimensional Gene Set Analysis.

Description

Classifies significant patterns form a Uni-Variate Gene Set Analysis.

Usage

uvPat(gsaout, cutoff = 0.05, pvalue = "padj", statistic = "lor")

Arguments

gsaout	data.frame; output from uvGsa.
cutoff	p-value cutoff for considering significant a Gene Set.
pvalue	p-value column to be used. Default is named "padj" as in uvGsa output.
statistic	name of the column containing the log odds ratio from the uvGsa analysis.

Details

Sign of the 'lor' and p-value are used to define functional blocks as up-regulated, down-regulated or not enriched.

Value

A numeric vector (values: -1, 0, 1) indicating relationship between the Gene Set and the ranking variable:

1:

indicates that the gene set is significantly associated to high values of the ranking statistic.

-1:

indicates that the gene set is significantly associated to low values of the ranking statistic.

0:

indicates that the gene set not related to the ranking statistic (no enrichment).

Author(s)

David Montaner [e-mail]

See Also

uvGsa, mdPat

Examples

uvGsa.res <- as.data.frame (list (N    = c (10, 20, 30, 40),
                                  lor  = c (1.45, -0.32, 1.89, -1.66),
                                  pval = c (0.001, 0.002, 0.05, 0.06)))
uvGsa.res[,"padj"] <- p.adjust (uvGsa.res$pval, "BY")
uvGsa.res

uvGsa.res[,"pat"] <- uvPat (uvGsa.res)
uvGsa.res

dmontaner/mdgsa documentation built on May 15, 2019, 9:35 a.m.