pathVar-package: Detects pathways with different levels of variance than...

In pathVar: Methods to Find Pathways with Significantly Different Variability

Description

This package contains functions used to determine pathways with significant differences in variability.

Details

Package:	pathVar
Type:	Package
Version:	1.11.2
Date:	2018-06-29
License:	LGPL
Depends:	R (>= 3.2.2), methods, ggplot2, gridExtra
Imports:	EMT, mclust, Matching, reshape, data.table

1. Compute the standard deviation for each gene. 2. Classify the genes with respect to sd in at most 4 clusters. 3. For each pathway, we extract the gene in our dataset and in which cluster they belong. 4. For each pathway, we look how its genes are distributed in each category and compare it to the expected number with all the gene from the dataset with the chisq. 5. Same as 4. but with the exact test 6. find significant pathway(s), which category(ies) from this pathway are significant and which gene(s) belongs to this(ese) category(ies)

Author(s)

Laurence de Torrente, Samuel Zimmerman, Jessica Mar

Examples

results_kegg=pathVarOneSample(bock,pways.kegg,test="chisq",varStat="sd")
sig_kegg=sigPway(results_kegg,0.05)

Example output

Loading required package: ggplot2
Loading required package: gridExtra

pathVar documentation built on Nov. 8, 2020, 5:47 p.m.