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PCR candidate region mismatch scanning: adaptation to quantitative, high-throughput genotyping

Nucleic Acids Research
Oxford University Press
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gkp536 1..10 Published online 24 June 2009 Nucleic Acids Research, 2009, Vol. 37, No. 17 e113 doi:10.1093/nar/gkp536 Extracting transcription factor targets from ChIP-Seq data Geetu Tuteja, Peter White, Jonathan Schug and Klaus H. Kaestner* Department of Genetics and Institute of Diabetes, Obesity and Metabolism, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA Received May 7, 2009; Revised and Accepted June 8, 2009 ABSTRACT ChIP-Seq technology, which combines chromatin immunoprecipitation (ChIP) with massively parallel sequencing, is rapidly replacing ChIP-on-chip for the genome-wide identification of transcription factor binding events. Identifying bound regions from the large number of sequence tags produced by ChIP-Seq is a challenging task. Here, we present GLITR (GLobal Identifier of Target Regions), which accurately identifies enriched regions in target data by calculating a fold-change based on random samples of control (input chromatin) data. GLITR uses a classification method to identify regions in ChIP data that have a peak height and fold-change which do not resemble regions in an input sample. We compare GLITR to several recent methods and show that GLITR has improved sensi- tivity for identifying bound regions closely matching the consensus sequence of a given transcription factor, and can detect bona fide transcription factor targets missed by other programs. We also use GLITR to address the issue of sequencing depth, and show that sequencing biological repli- cates identifies far more binding regions than re-sequencing the same sample. INTRODUCTION Chromatin immunoprecipitation, or ‘ChIP’, allows for the capture of the binding events between transcription factors or other DNA binding proteins and their targets in vivo at the moment of biochemical cross-linking. With the development of ‘ChIP-on-chip’ technology, the near genome-wide location analysis of binding sites for transcription factors became a reality (1). While this tech- nology ha

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