SeqGL identifies context-dependent binding signals in genome-wide regulatory element maps Journal Article


Authors: Setty, M.; Leslie, C. S.
Article Title: SeqGL identifies context-dependent binding signals in genome-wide regulatory element maps
Abstract: Genome-wide maps of transcription factor (TF) occupancy and regions of open chromatin implicitly contain DNA sequence signals for multiple factors. We present SeqGL, a novel de novo motif discovery algorithm to identify multiple TF sequence signals from ChIP-, DNase-, and ATAC-seq profiles. SeqGL trains a discriminative model using a k-mer feature representation together with group lasso regularization to extract a collection of sequence signals that distinguish peak sequences from flanking regions. Benchmarked on over 100 ChIP-seq experiments, SeqGL outperformed traditional motif discovery tools in discriminative accuracy. Furthermore, SeqGL can be naturally used with multitask learning to identify genomic and cell-type context determinants of TF binding. SeqGL successfully scales to the large multiplicity of sequence signals in DNase- or ATAC-seq maps. In particular, SeqGL was able to identify a number of ChIP-seq validated sequence signals that were not found by traditional motif discovery algorithms. Thus compared to widely used motif discovery algorithms, SeqGL demonstrates both greater discriminative accuracy and higher sensitivity for detecting the DNA sequence signals underlying regulatory element maps. SeqGL is available at © 2015 Setty, Leslie.
Keywords: sequence analysis; sensitivity analysis; accuracy; transcription factor; gene mapping; chromatin immunoprecipitation; genomics; dna flanking region; dna sequence; genetic algorithm; dna binding motif; deoxyribonuclease; adenine; thymine; regulatory sequence; cytosine; human; article; sequence database; seqgl
Journal Title: PLoS Computational Biology
Volume: 11
Issue: 5
ISSN: 1553-7358
Publisher: Public Library of Science  
Date Published: 2015-05-27
Start Page: e1004271
Language: English
DOI: 10.1371/journal.pcbi.1004271
PROVIDER: scopus
PMCID: PMC4446265
PUBMED: 26016777
DOI/URL:
Notes: Export Date: 2 July 2015 -- Source: Scopus
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  1. Christina Leslie
    191 Leslie
  2. Manu Setty
    35 Setty