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Comparative study on ChIP-seq data: normalization and binding pattern characterization
Author(s) -
Cenny Taslim,
Jiejun Wu,
Pearlly S. Yan,
Greg Singer,
Jeffrey D. Parvin,
Tim H.M. Huang,
Shili Lin,
Kun Huang
Publication year - 2009
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btp384
Subject(s) - normalization (sociology) , computer science , computational biology , data mining , biology , sociology , anthropology
Antibody-based Chromatin Immunoprecipitation assay followed by high-throughput sequencing technology (ChIP-seq) is a relatively new method to study the binding patterns of specific protein molecules over the entire genome. ChIP-seq technology allows scientist to get more comprehensive results in shorter time. Here, we present a non-linear normalization algorithm and a mixture modeling method for comparing ChIP-seq data from multiple samples and characterizing genes based on their RNA polymerase II (Pol II) binding patterns.

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