normalizePval: This function normalizes p-values (Scores) that are otherwise...

In AJEinstein/SMITE: Significance-based Modules Integrating the Transcriptome and Epigenome

Description

This function is a used to rescale compenent scores when distributions have been altered. There are two methods available.

Usage

normalizePval(pvalue_annotation, trans, ref = "expression_pvalue", method = "rescale")

Arguments

pvalue_annotation	An S4 object of class p-value annotation
trans	A vector specifying a specific Box-cox power transformation to use. If not specified, the optimal transformation powers will be estimated.
ref	A string that will be grepped from the names of the loaded expression data or modification/context pairing. All scores will be rescaled to match this reference's range. The DEFAULT is expression.
method	A string of either "Rescale" DEFAULT "rescale" Performs a logit transform and rescales all probabilites to the reference's logit transformed scale, then back-transforms "Box-Cox" "box-cox" "boxcox" "Boxcox" For each probility vector does a logit transform and then iterates between 0.5 and 0.95 by 0.05 to determine the most similar transformation to the logit transformed referece by a Wilcoxon- test

Details

Normalization may not be necessary but should improve some p-values from driving the majority of downstream scores and modules solely because of the scale of their p-values. All transformations are monotonic and are controlled for by use of randomization prodecure downstream. procedures downstream should

Value

An S4 object of class PvalueAnnotation with normalized p-values withing the pval_data slot of the PvalueObject "score_data" slot

Plots densities of p-values before and after transform

Author(s)

N. Ari Wijetunga

See Also

makePvalueObject scorePval plotDensityPval

Examples

data(test_annotation_score_data)

#test_annotation<-normalizePval(pvalue_annotation=test_annotation)

AJEinstein/SMITE documentation built on Oct. 23, 2021, 7:44 a.m.