A1 Refereed original research article in a scientific journal
Optimizing Detection of Transcription Factor-Binding Sites in ChIP-seq Experiments
Authors: Elo LL, Kallio A, Laajala TD, Hawkins RD, Korpelainen E, Aittokallio T
Editors: Noam Shomron
Publisher: OXFORD UNIV PRESS
Publication year: 2012
Journal: Nucleic Acids Research
Book title : Deep Sequencing Data Analysis
Journal name in source: NUCLEIC ACIDS RESEARCH
Journal acronym: NUCLEIC ACIDS RES
Article number: ARTN e1
Number in series: 1
Volume: 40
Issue: 1
Number of pages: 11
ISBN: 978-1-62703-513-2
ISSN: 0305-1048
DOI: https://doi.org/10.1093/nar/gkr839(external)
Abstract
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.
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.
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