title: Saturation analysis of ChIP-seq data for reproducible identification of binding peaks.
abstract: Chromatin immunoprecipitation coupled with next-generation sequencing (ChIP-seq) is a powerful technology to identify the genome-wide locations of transcription factors and other DNA binding proteins. Computational ChIP-seq peak calling infers the location of protein-DNA interactions based on various measures of enrichment of sequence reads. In this work, we introduce an algorithm, Q, that uses an assessment of the quadratic enrichment of reads to center candidate peaks followed by statistical analysis of saturation of candidate peaks by 5' ends of reads. We show that our method not only is substantially faster than several competing methods but also demonstrates statistically significant advantages with respect to reproducibility of results and in its ability to identify peaks with reproducible binding site motifs. We show that Q has superior performance in the delineation of double RNAPII and H3K4me3 peaks surrounding transcription start sites related to a better ability to resolve individual peaks. The method is implemented in C++ and is freely available under an open source license.
authors.affiliation: Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany; Berlin Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany;
authors.forename: Peter
authors.initials: P
authors.lastname: Hansen
authors.affiliation: Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany; Berlin Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany; Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany;
authors.forename: Jochen
authors.initials: J
authors.lastname: Hecht
authors.affiliation: Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany; Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany;
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Ibrahim
authors.affiliation: Department of Biostatistics, Clinical Research Unit, Berlin Institute of Health, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany;
authors.forename: Alexander
authors.initials: A
authors.lastname: Krannich
authors.affiliation: Labor für Pädiatrische Molekularbiologie, Charité-Universitätsmedizin Berlin, 10117, Berlin, Germany;
authors.forename: Matthias
authors.initials: M
authors.lastname: Truss
authors.affiliation: Institute for Medical and Human Genetics, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany; Berlin Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany; Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany; Institute for Bioinformatics, Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany.
authors.forename: Peter N
authors.initials: PN
authors.lastname: Robinson
mesh_terms: D000465:Algorithms; D001665:Binding Sites / Q000235:genetics; D047369:Chromatin Immunoprecipitation; D004268:DNA-Binding Proteins; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D059372:Nucleotide Motifs; D011485:Protein Binding; D015203:Reproducibility of Results; D014157:Transcription Factors / Q000378:metabolism; D024363:Transcription Initiation Site
chemical_list: D004268:DNA-Binding Proteins; D014157:Transcription Factors