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Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool

Motivation: Biological analysis has shifted from identifying genes and transcripts to mapping these genes and transcripts to biological functions. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a...

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Detalles Bibliográficos
Autores principales: Auerbach, Raymond K., Chen, Bin, Butte, Atul J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3712221/
https://www.ncbi.nlm.nih.gov/pubmed/23732275
http://dx.doi.org/10.1093/bioinformatics/btt316
Descripción
Sumario:Motivation: Biological analysis has shifted from identifying genes and transcripts to mapping these genes and transcripts to biological functions. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a biomedical scientist to analyze these data are either non-existent or tailored to narrow biological questions. We present the ENCODE ChIP-Seq Significance Tool, a flexible web application leveraging public ENCODE data to identify enriched transcription factors in a gene or transcript list for comparative analyses. Implementation: The ENCODE ChIP-Seq Significance Tool is written in JavaScript on the client side and has been tested on Google Chrome, Apple Safari and Mozilla Firefox browsers. Server-side scripts are written in PHP and leverage R and a MySQL database. The tool is available at http://encodeqt.stanford.edu. Contact: abutte@stanford.edu Supplementary information: Supplementary material is available at Bioinformatics online.