Ontology type: schema:ScholarlyArticle Open Access: True
2008-09-17
AUTHORSYong Zhang, Tao Liu, Clifford A Meyer, Jérôme Eeckhoute, David S Johnson, Bradley E Bernstein, Chad Nusbaum, Richard M Myers, Myles Brown, Wei Li, X Shirley Liu
ABSTRACTWe present Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer. MACS empirically models the shift size of ChIP-Seq tags, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions. MACS compares favorably to existing ChIP-Seq peak-finding algorithms, and is freely available. More... »
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http://scigraph.springernature.com/pub.10.1186/gb-2008-9-9-r137
DOIhttp://dx.doi.org/10.1186/gb-2008-9-9-r137
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PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/18798982
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