ComputeMotifScore: Compute the scores for SNP effects on motifs.

In kinsigne/atSNP_modified: Affinity test for identifying regulatory SNPs.

Description

Compute the log-likelihood scores for motifs.

Usage

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.table'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)

Chandler [e-mail]

Examples

data(example)
ComputeMotifScore(motif_library, snpInfo, ncores = 2)

kinsigne/atSNP_modified documentation built on May 23, 2019, 4:24 p.m.