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  Transcription factor binding predictions using TRAP for the analysis of ChIP-seq data and regulatory SNPs

Thomas-Chollier, M., Hufton, A., Heinig, M., O'Keeffe, S., Masri, N. E., Roider, H. G., et al. (2011). Transcription factor binding predictions using TRAP for the analysis of ChIP-seq data and regulatory SNPs. Nat Protoc, 6(12), 1860-9. Retrieved from http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=22051799 http://www.nature.com/nprot/journal/v6/n12/pdf/nprot.2011.409.pdf.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7934-3 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-7935-1
Genre: Journal Article

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Thomas-Chollier, M.1, Author              
Hufton, A.2, Author              
Heinig, M.1, Author              
O'Keeffe, S., Author
Masri, N. E., Author
Roider, H. G.1, Author              
Manke, T.1, Author              
Vingron, M.3, Author              
Affiliations:
1Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              
2Evolution and Development (Albert Poustka), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479650              
3Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479639              

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 Abstract: The transcription factor affinity prediction (TRAP) method calculates the affinity of transcription factors for DNA sequences on the basis of a biophysical model. This method has proven to be useful for several applications, including for determining the putative target genes of a given factor. This protocol covers two other applications: (i) determining which transcription factors have the highest affinity in a set of sequences (illustrated with chromatin immunoprecipitation-sequencing (ChIP-seq) peaks), and (ii) finding which factor is the most affected by a regulatory single-nucleotide polymorphism. The protocol describes how to use the TRAP web tools to address these questions, and it also presents a way to run TRAP on random control sequences to better estimate the significance of the results. All of the tools are fully available online and do not need any additional installation. The complete protocol takes about 45 min, but each individual tool runs in a few minutes.

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 Dates: 2011
 Publication Status: Published in print
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Title: Nat Protoc
Source Genre: Journal
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Pages: - Volume / Issue: 6 (12) Sequence Number: - Start / End Page: 1860 - 9 Identifier: ISSN: 1750-2799 (Electronic) 1750-2799 (Linking)