SArKS: de novo discovery of gene expression regulatory motif sites and domains by suffix array kernel smoothing.

ABSTRACT:

Motivation

We set out to develop an algorithm that can mine differential gene expression data to identify candidate cell type-specific DNA regulatory sequences. Differential expression is usually quantified as a continuous score-fold-change, test-statistic, P-value-comparing biological classes. Unlike existing approaches, our de novo strategy, termed SArKS, applies non-parametric kernel smoothing to uncover promoter motif sites that correlate with elevated differential expression scores. SArKS detects motif k-mers by smoothing sequence scores over sequence similarity. A second round of smoothing over spatial proximity reveals multi-motif domains (MMDs). Discovered motif sites can then be merged or extended based on adjacency within MMDs. False positive rates are estimated and contr

SUBMITTER: Wylie DC 

PROVIDER: S-EPMC7963082 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature