Syndicated from PubMed RSS Feeds
A short survey of computational analysis methods in analysing ChIP-seq data.
Hum Genomics. 2011 Jan 1;5(2):117-23
Authors: Kim H, Kim J, Selby H, Gao D, Tong T, Phang TL, Tan AC
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.
PMID: 21296745 [PubMed - in process]
More...
A short survey of computational analysis methods in analysing ChIP-seq data.
Hum Genomics. 2011 Jan 1;5(2):117-23
Authors: Kim H, Kim J, Selby H, Gao D, Tong T, Phang TL, Tan AC
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.
PMID: 21296745 [PubMed - in process]
More...