Abstract
Chromatin immunoprecipitation followed by massively parallel next-generation sequencing (ChIP-seq) is a valuable experimental strategy for assaying protein-DNA interaction over the whole genome. Many computational tools have been designed to find the peaks of the signals corresponding to protein binding sites. In this paper, three computational methods, ChIP-seq processing pipeline (spp), PeakSeq and CisGenome, used in ChIP-seq data analysis are reviewed. There is also a comparison of how they agree and disagree on finding peaks using the publically available Signal Transducers and Activators of Transcription protein 1 (STAT1) and RNA polymerase II (PolII) datasets with corresponding negative controls.
Original language | English |
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Pages (from-to) | 117-123 |
Number of pages | 7 |
Journal | Human Genomics |
Volume | 5 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2011 Jan |
Bibliographical note
Funding Information:We would like to thank Dr David L. Bentley for his constructive comments on the initial draft of this manuscript. H.K. is supported by NIH grant to GM063873 to D.L. Bentley.
Keywords
- Bioinformatics
- CHIP-Seq analysis
- Comparative analysis
- Next-generation sequencing
ASJC Scopus subject areas
- Molecular Medicine
- Molecular Biology
- Genetics
- Drug Discovery