FunciSNP-package: Functional Identification of SNPs with Phenotype by...

In shraddhapai/FunciSNP: Integrating Functional Non-coding Datasets with Genetic Association Studies to Identify Candidate Regulatory SNPs

Description

The package includes functions to identify and annotate putative functional SNPs using information derived from GWAS, 1000 genomes database, and sequences around peaks.

Details

Package:	FunciSNP
Type:	Package
Version:	0.99.0
Date:	2012-05-18
License:	GPL-3
LazyLoad:	yes

Author(s)

Simon G. Coetzee (maintainer: [e-mail]); Houtan Noushmehr, PhD ([e-mail])

References

SG. Coetzee, SK. Rhie, BP. Berman, GA. Coetzee and H. Noushmehr, FunciSNP: An R/Bioconductor Tool Integrating Functional Non-coding Datasets with Genetic Association Studies to Identify Candidate Regulatory SNPs., Nucleic Acids Research, In press, 2012 (doi:10.1093/nar/gks542).

See Also

FunciSNPplot, FunciSNPAnnotateSummary, FunciSNPtable, FunciSNPbed

Examples

##
## Glioblastoma analysis using FunciSNP
##
## Full path to the example regions file for Glioblastoma 
#  (collected from SNPedia)
glioma.snp <- file.path(system.file('extdata',
  package='FunciSNP'),
  dir(system.file('extdata',package='FunciSNP'), 
  pattern='.snp$'));
 
## Full path to the example biological features BED files 
#  derived from the ENCODE project for Glioblastoma U-87 
#  cell lines.
glioma.bio <- system.file('extdata',package='FunciSNP');

## FunciSNP analysis, extracts correlated SNPs from the 
#  1000 genomes db ("ncbi") and finds overlaps between 
#  correlated SNP and biological features and then 
#  calculates LD (Rsquare, Dprime, distance, p-value).
# Do not run. Can take more than 5 min depending on internet connection and number of CPUs.
#glioma <- FunciSNP(snp.regions.file=glioma.snp, 
#  bio.features.loc = glioma.bio, bio.features.TSS=FALSE);

##
data(glioma);
class(glioma);
glioma;
summary(glioma);

shraddhapai/FunciSNP documentation built on May 29, 2019, 9:26 p.m.