Discriminative motif analysis of high-throughput dataset.

ABSTRACT:

Motivation

High-throughput ChIP-seq studies typically identify thousands of peaks for a single transcription factor (TF). It is common for traditional motif discovery tools to predict motifs that are statistically significant against a naïve background distribution but are of questionable biological relevance.

Results

We describe a simple yet effective algorithm for discovering differential motifs between two sequence datasets that is effective in eliminating systematic biases and scalable to large datasets. Tested on 207 ENCODE ChIP-seq datasets, our method identifies correct motifs in 78% of the datasets with known motifs, demonstrating improvement in both accuracy and efficiency compared with DREME, another state-of-art discriminative motif discovery tool. More interestin

SUBMITTER: Yao Z 

PROVIDER: S-EPMC3957073 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature