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Oxford University Press, Bioinformatics, 2(34), p. 303-305, 2017

DOI: 10.1093/bioinformatics/btx570

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SiNoPsis: Single Nucleotide Polymorphisms selection and promoter profiling

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Abstract Motivation The selection of a single nucleotide polymorphism (SNP) using bibliographic methods can be a very time-consuming task. Moreover, a SNP selected in this way may not be easily visualized in its genomic context by a standard user hoping to correlate it with other valuable information. Here we propose a web form built on top of Circos that can assist SNP-centered screening, based on their location in the genome and the regulatory modules they can disrupt. Its use may allow researchers to prioritize SNPs in genotyping and disease studies. Results SiNoPsis is bundled as a web portal. It focuses on the different structures involved in the genomic expression of a gene, especially those found in the core promoter upstream region. These structures include transcription factor binding sites (for promoter and enhancer signals), histones and promoter flanking regions. Additionally, the tool provides eQTL and linkage disequilibrium (LD) properties for a given SNP query, yielding further clues about other indirectly associated SNPs. Possible disruptions of the aforementioned structures affecting gene transcription are reported using multiple resource databases. SiNoPsis has a simple user-friendly interface, which allows single queries by gene symbol, genomic coordinates, Ensembl gene identifiers, RefSeq transcript identifiers and SNPs. It is the only portal providing useful SNP selection based on regulatory modules and LD with functional variants in both textual and graphic modes (by properly defining the arguments and parameters needed to run Circos). Availability and implementation SiNoPsis is freely available at https://compgen.bio.ub.edu/SiNoPsis/ Supplementary information Supplementary data are available at Bioinformatics online.