ComputeMotifScore: Compute the scores for SNP effects on motifs.

Description Usage Arguments Details Value Author(s) Examples

View source: R/motif_analysis.R

Description

Compute the log-likelihood scores for motifs.

Usage

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ComputeMotifScore(motif.lib, snp.info, ncores = 1)

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.

ncores

An integer for the number of parallel process. Default: 1.

Details

This function computes the binding affinity scores for both alleles at each SNP window. For each pair of SNP and motif, it finds the subsequence from both strand that maximizes the affinity binding score. It returns both the matching positions and the maximized affinity scores.

Value

A list of two data.frame's. Field snp.tbl contains:

snpid SNP id.
ref_seq Reference allele nucleotide sequence.
snp_seq SNP allele nucleotide sequence.
ref_seq_rev Reference allele nucleotide sequence on the reverse strand.
snp_seq_rev SNP allele nucleotide sequence on the reverse strand.

Field motif.score contains:

motif Name of the motif.
motif_len Length of the motif.
ref_start, ref_end, ref_strand Location of the best matching subsequence on the reference allele.
snp_start, snp_end, snp_strand Location of the best matching subsequence on the SNP allele.
log_lik_ref Log-likelihood score for the reference allele.
log_lik_snp Log-likelihood score for the SNP allele.
log_lik_ratio The log-likelihood ratio.
log_enhance_odds Difference in log-likelihood ratio between SNP allele and reference allele based on the best matching subsequence on the reference allele.
log_reduce_odds Difference in log-likelihood ratio between reference allele and SNP allele based on the best matching subsequence on the SNP allele.

Author(s)

Sunyoung Shin sunyoung.shin@utdallas.edu, Chandler Zuo chandler.c.zuo@gmail.com

Examples

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