FunciSNP: an R/bioconductor tool integrating functional non-coding data sets with genetic association studies to identify candidate regulatory SNPs

Abstract

Single nucleotide polymorphisms (SNPs) are increasingly used to tag genetic loci associated with phenotypes such as risk of complex diseases. Technically, this is done genome-wide without prior restriction or knowledge of biological feasibility in scans referred to as genome-wide association studies (GWAS). Depending on the linkage disequilibrium (LD) structure at a particular locus, such tagSNPs may be surrogates for many thousands of other SNPs, and it is difficult to distinguish those that may play a functional role in the phenotype from those simply genetically linked. Because a large proportion of tagSNPs have been identified within non-coding regions of the genome, distinguishing functional from non-functional SNPs has been an even greater challenge. A strategy was recently proposed that prioritizes surrogate SNPs based on non-coding chromatin and epigenomic mapping techniques that have become feasible with the advent of massively parallel sequencing. Here, we introduce an R/Bioconductor software package that enables the identification of candidate functional SNPs by integrating information from tagSNP locations, lists of linked SNPs from the 1000 genomes project and locations of chromatin features which may have functional significance. Availability: FunciSNP is available from Bioconductor (bioconductor.org).

Genome-wide association study identifies a new susceptibility locus for cleft lip with or without a cleft palate

“…To investigate the underlying mechanisms of the lead SNPs identified in our studies, we integrated chromatin biofeature annotations with 1,000 Genomes genotyping data using the Bioconductor R package FunciSNP 31 . The following resources were employed to filter the correlated SNPs lying within putative regulatory elements: (1) Roadmap: Chromatin Primary Core Marks Segmentation by HMM from H1 cell lines and hESH1-derived mesenchymal cells; (2) Fantom: an active, in vivo-transcribed enhancers atlas 32 ; (3) Enhancer identified in a previously published paper 33 .…”

FunSeq2: A framework for prioritizing noncoding regulatory variants in cancer

“…Studies have shown that disease-associated single nucleotide polymorphisms (SNPs) identified by Genome-wide Association Studies (GWAS) are significantly enriched in ENCODE regions [17]. A number of tools have been developed using these data to annotate potential regulatory variants or to suggest the most likely causal variants in linkage disequilibrium with GWAS SNPs, such as Haploreg [18], RegulomeDB [19], ANNOVAR [20], GEMINI [21], FunciSNP [22], and VEP [23]. Recently, two computational approaches -GWAVA and CADD -were published to predict the deleterious effect of variants genome-wide [24,25].…”

A rare variant, which destroys a FoxA1 site at 8q24, is associated with prostate cancer risk

“…1 It is unclear what function can be ascribed to rs188140481 due to lack of evidence for chromatin biological features at its genomic location. We used FunciSNP, 2 an R/Bioconductor software package developed by us, to analyze this novel index SNP for correlated SNPs within known biological/chromatin features from recently published high-throughput data. Our analysis resulted in the identification of a single correlated SNP, rs183373024, which was also identified by Gudmundsson et al, 1 but rejected as a candidate for further study on the basis that it is highly correlated with the index SNP rs188140481 (r 2 = 0.87), while having slightly weaker combined replication results.…”