A1 Refereed original research article in a scientific journal

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




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

EditorsNoam Shomron

PublisherOXFORD UNIV PRESS

Publication year2012

JournalNucleic Acids Research

Book title Deep Sequencing Data Analysis

Journal name in sourceNUCLEIC ACIDS RESEARCH

Journal acronymNUCLEIC ACIDS RES

Article numberARTN e1

Number in series1

Volume40

Issue1

Number of pages11

ISBN978-1-62703-513-2

ISSN0305-1048

DOIhttps://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.



Last updated on 2024-26-11 at 18:00