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PLoS One. 2010 Jul 8;5(7):e11471. doi: 10.1371/journal.pone.0011471.

Evaluation of algorithm performance in ChIP-seq peak detection.

Author information

1
Graduate Group in Microbiology, University of California Davis, Davis, California, United States of America.

Abstract

Next-generation DNA sequencing coupled with chromatin immunoprecipitation (ChIP-seq) is revolutionizing our ability to interrogate whole genome protein-DNA interactions. Identification of protein binding sites from ChIP-seq data has required novel computational tools, distinct from those used for the analysis of ChIP-Chip experiments. The growing popularity of ChIP-seq spurred the development of many different analytical programs (at last count, we noted 31 open source methods), each with some purported advantage. Given that the literature is dense and empirical benchmarking challenging, selecting an appropriate method for ChIP-seq analysis has become a daunting task. Herein we compare the performance of eleven different peak calling programs on common empirical, transcription factor datasets and measure their sensitivity, accuracy and usability. Our analysis provides an unbiased critical assessment of available technologies, and should assist researchers in choosing a suitable tool for handling ChIP-seq data.

PMID:
20628599
PMCID:
PMC2900203
DOI:
10.1371/journal.pone.0011471
[Indexed for MEDLINE]
Free PMC Article

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