ComputePValues: Compute p-values for affinity scores.

In atSNP: Affinity test for identifying regulatory SNPs

Description

This function computes the p-values for allele-specific affinity scores and between-allele affinity score changes using the importance sampling technique.

Usage

ComputePValues(motif.lib, snp.info, motif.scores, ncores = 1,
  testing.mc = FALSE, figdir = NULL)

Arguments

motif.lib	A list object with the output format of function LoadMotifLibrary.
snp.info	A list object with the output format of function LoadSNPData.
motif.scores	A data.frame object containing at least the following columns: motif The name of the motif. log_lik_ref The log-likelihood score for the reference allele. log_lik_snp The log-likelihood score for the SNP allele.
ncores	An integer for the number of parallel process. Default: 1.
testing.mc	Monte Carlo sample size of 200 is considered. Do not change the default unless conducting a quick test. Default: FALSE
figdir	A string for the path to print p-value plots for monitoring results. Default: NULL (no figure).

Value

A data.frame extending motif.scores by the following additional columns:

pval_ref	P-values for scores on the reference allele.
pval_snp	P-values for scores on the SNP allele.
pval_cond_ref	Conditional p-values for scores on the reference allele.
pval_cond_snp	Conditional p-values for scores on the SNP allele.
pval_diff	P-values for the difference in scores between the reference and the SNP alleles.
pval_rank	P-values for the log rank ratio between the reference and the SNP alleles.

Author(s)

Sunyoung Shin [e-mail], Chandler Zuo [e-mail]

Examples

data(example)
ComputePValues(motif_library, snpInfo, motif_scores$motif.scores, ncores = 2, testing.mc=TRUE)

atSNP documentation built on April 28, 2020, 6:50 p.m.