A1 Refereed original research article in a scientific journal

snpEnrichR: analyzing co-localization of SNPs and their proxies in genomic regions




AuthorsKari Nousiainen, Kartiek Kanduri, Isis Ricaño-Ponce, Cisca Wijmenga, Riitta Lahesmaa, Vinod Kumar, Harri Lähdesmäki

Publication year2018

JournalBioinformatics

Article numberbty460

Volume34

Issue23

First page 4112

Last page4114

Number of pages3

ISSN1367-4803

eISSN1460-2059

DOIhttps://doi.org/10.1093/bioinformatics/bty460

Web address https://academic.oup.com/bioinformatics/article/34/23/4112/5034433

Self-archived copy’s web addresshttps://research.utu.fi/converis/portal/detail/Publication/33334184


Abstract
Motivation:

Co-localization of trait associated SNPs for
specific transcription-factor binding sites or regulatory regions in the
genome can yield profound insight into underlying causal mechanisms.
Analysis is complicated because the truly causal SNPs are generally
unknown and can be either SNPs reported in GWAS studies or other proxy
SNPs in their linkage disequilibrium. Hence, a comprehensive pipeline
for SNP co-localization analysis that utilizes all relevant information
about both the genotyped SNPs and their proxies is needed.

Results:

We
developed an R package snpEnrichR for SNP co-localization analysis. The
software integrates different tools for random SNP generation and
genome co-localization analysis to automatize and help users to create
custom SNP co-localization analysis. We show via an example that
including proxy SNPs in SNP co-localization analysis enhances the
sensitivity of co-localization detection.

Availability:

The software is available at https://github.com/kartiek/snpEnrichR.


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Last updated on 2024-26-11 at 11:13