title: Using combined evidence from replicates to evaluate ChIP-seq peaks.
abstract: BACKGROUND
  Chromatin Immunoprecipitation followed by sequencing (ChIP-seq) detects genome-wide DNA-protein interactions and chromatin modifications, returning enriched regions (ERs), usually associated with a significance score. Moderately significant interactions can correspond to true, weak interactions, or to false positives; replicates of a ChIP-seq experiment can provide co-localised evidence to decide between the two cases. We designed a general methodological framework to rigorously combine the evidence of ERs in ChIP-seq replicates, with the option to set a significance threshold on the repeated evidence and a minimum number of samples bearing this evidence.
  
  
  RESULTS
  We applied our method to Myc transcription factor ChIP-seq datasets in K562 cells available in the ENCODE project. Using replicates, we could extend up to 3 times the ER number with respect to single-sample analysis with equivalent significance threshold. We validated the 'rescued' ERs by checking for the overlap with open chromatin regions and for the enrichment of the motif that Myc binds with strongest affinity; we compared our results with alternative methods (IDR and jMOSAiCS), obtaining more validated peaks than the former and less peaks than latter, but with a better validation.
  
  
  METHODS
  An implementation of the proposed method and its source code under GPLv3 license are freely available at http://www.bioinformatics.deib.polimi.it/MSPC/ and http://mspc.codeplex.com/, respectively.
  
  
  BACKGROUND
  marco.morelli@iit.it
  
  
  BACKGROUND
  Supplementary Material are available at Bioinformatics online.
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan, Italy and.
authors.forename: Vahid
authors.initials: V
authors.lastname: Jalili
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan, Italy and.
authors.forename: Matteo
authors.initials: M
authors.lastname: Matteucci
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milan, Italy and.
authors.forename: Marco
authors.initials: M
authors.lastname: Masseroli
authors.affiliation: Center for Genomic Science of IIT@SEMM, Istituto Italiano di Tecnologia (IIT), 20139 Milan, Italy.
authors.forename: Marco J
authors.initials: MJ
authors.lastname: Morelli
mesh_terms: D000465:Algorithms; D002843:Chromatin / Q000235:genetics / Q000378:metabolism*; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D019295:Computational Biology / Q000379:methods; D003627:Data Interpretation, Statistical; D005786:Gene Expression Regulation; D015894:Genome, Human; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D020014:K562 Cells; D059372:Nucleotide Motifs / Q000235:genetics; D011485:Protein Binding; D017434:Protein Structure, Tertiary; D016271:Proto-Oncogene Proteins c-myc / Q000235:genetics / Q000378:metabolism; D011786:Quality Control; D015203:Reproducibility of Results; D017422:Sequence Analysis, DNA; D012984:Software; D014157:Transcription Factors / Q000378:metabolism*; D044767:Ubiquitin-Protein Ligases / Q000235:genetics / Q000378:metabolism*
chemical_list: D002843:Chromatin; C489427:MYC protein, human; D016271:Proto-Oncogene Proteins c-myc; D014157:Transcription Factors; C467728:STUB1 protein, human; D044767:Ubiquitin-Protein Ligases