Optimized detection of transcription factor-binding sites in ChIP-seq experiments.
We developed a computational procedure for optimizing the binding site detections in a given ChIP-seq experiment by maximizing their reproducibility under bootstrap sampling. We demonstrate how the procedure can improve the detection accuracies beyond those obtained with the default settings of popular peak calling software, or inform the user whether the peak detection results are compromised, circumventing the need for arbitrary re-iterative peak calling under varying parameter settings. The generic, open-source implementation is easily extendable to accommodate additional features and to promote its widespread application in future ChIP-seq studies. The peakROTS R-package and user guide are freely available at http://www.nic.funet.fi/pub/sci/molbio/peakROTS.
Department of Mathematics, University of Turku, FI-20014 Turku, Finland. laliel@utu.fi
Laura L
LL
Elo
Aleksi
A
Kallio
Teemu D
TD
Laajala
R David
RD
Hawkins
Eija
E
Korpelainen
Tero
T
Aittokallio
D000818:Animals; D001665:Binding Sites; D047369:Chromatin Immunoprecipitation / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D051379:Mice; D017422:Sequence Analysis, DNA; D012984:Software; D014157:Transcription Factors / Q000032:analysis*
D014157:Transcription Factors