Optimizing Detection of Transcription Factor-Binding Sites in ChIP-seq Experiments

: Elo LL, Kallio A, Laajala TD, Hawkins RD, Korpelainen E, Aittokallio T

: Noam Shomron

Publisher: OXFORD UNIV PRESS

: 2012

: Nucleic Acids Research

: Deep Sequencing Data Analysis

: NUCLEIC ACIDS RESEARCH

: NUCLEIC ACIDS RES

: ARTN e1

: 1

: 40

: 1

: 11

: 978-1-62703-513-2

: 0305-1048

DOI: https://doi.org/10.1093/nar/gkr839

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.