MANTA2, update of the Mongo database for the analysis of transcription factor binding site alterations View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-07-24

AUTHORS

Oriol Fornes, Marius Gheorghe, Phillip A. Richmond, David J. Arenillas, Wyeth W. Wasserman, Anthony Mathelier

ABSTRACT

Interpreting the functional impact of noncoding variants is an ongoing challenge in the field of genome analysis. With most noncoding variants associated with complex traits and disease residing in regulatory regions, altered transcription factor (TF) binding has been proposed as a mechanism of action. It is therefore imperative to develop methods that predict the impact of noncoding variants at TF binding sites (TFBSs). Here, we describe the update of our MANTA database that stores: 1) TFBS predictions in the human genome, and 2) the potential impact on TF binding for all possible single nucleotide variants (SNVs) at these TFBSs. TFBSs were predicted by combining experimental ChIP-seq data from ReMap and computational position weight matrices (PWMs) derived from JASPAR. Impact of SNVs at these TFBSs was assessed by means of PWM scores computed on the alternate alleles. The updated database, MANTA2, provides the scientific community with a critical map of TFBSs and SNV impact scores to improve the interpretation of noncoding variants in the human genome. More... »

PAGES

180141

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/sdata.2018.141

DOI

http://dx.doi.org/10.1038/sdata.2018.141

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1105775300

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30040077


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43 schema:description Interpreting the functional impact of noncoding variants is an ongoing challenge in the field of genome analysis. With most noncoding variants associated with complex traits and disease residing in regulatory regions, altered transcription factor (TF) binding has been proposed as a mechanism of action. It is therefore imperative to develop methods that predict the impact of noncoding variants at TF binding sites (TFBSs). Here, we describe the update of our MANTA database that stores: 1) TFBS predictions in the human genome, and 2) the potential impact on TF binding for all possible single nucleotide variants (SNVs) at these TFBSs. TFBSs were predicted by combining experimental ChIP-seq data from ReMap and computational position weight matrices (PWMs) derived from JASPAR. Impact of SNVs at these TFBSs was assessed by means of PWM scores computed on the alternate alleles. The updated database, MANTA2, provides the scientific community with a critical map of TFBSs and SNV impact scores to improve the interpretation of noncoding variants in the human genome.
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