snpEnrichment (version 1.6.0)

snpEnrichment-package: ~ Overview: SNPs enrichment analysis ~

Description

Implements classes and methods for large-scale SNP enrichment analysis (e.g. SNPs associated with genes expression in a GWAS signal).

Details

ll{ Package: snpEnrichment Title: SNPs enrichment analysis Author: Mickael Canouil Contributor: Loic Yengo Maintainer: Mickael Canouil License: GPL (>= 2) Depends: R (>= 3.0.0), methods Suggests: grid, ggplot2 Imports: parallel, snpStats URL: https://github.com/mcanouil/snpEnrichment Encoding: UTF-8 }

See Also

Overview : snpEnrichment-package Classes : Enrichment, Chromosome, EnrichSNP Methods : plot, reSample, getEnrichSNP, excludeSNP, compareEnrichment, enrichment, is.enrichment, chromosome, is.chromosome Functions : initFiles, writeLD, readEnrichment

Examples

###################
### 1. Prepare data
snpInfoDir <- system.file("extdata/snpInfo",
                          package = "snpEnrichment")
signalFile <- system.file("extdata/Signal/toySignal.txt",
                          package = "snpEnrichment")

initFiles(pattern = "Chrom", snpInfoDir, signalFile, mc.cores = 1)

writeLD(pattern = "Chrom", snpInfoDir, signalFile,
        ldDir = NULL, ldThresh = 0.8, depth = 1000,
        mc.cores = 1)


################
### 2. Read data
snpListDir <- system.file("extdata/List",
                          package = "snpEnrichment")
data(transcript)
transcriptFile <- transcript

toyData <- readEnrichment(pattern = "Chrom", signalFile,
                         transcriptFile, snpListDir,
                         snpInfoDir, distThresh = 1000,
                         sigThresh = 0.05, LD = TRUE,
                         ldDir = NULL, mc.cores = 1)
toyData


######################
### 3. Compute results
reSample(object = toyData,
         nSample = 10,
         empiricPvalue = TRUE,
         MAFpool = c(0.05, 0.10, 0.2, 0.3, 0.4, 0.5),
         mc.cores = 1,
         onlyGenome = TRUE)


#######################
### 4. Further analysis: Exclude SNP from original list.
excludeFile <- c(
    "rs4376885", "rs17690928", "rs6460708", "rs13061537", "rs11769827",
    "rs12717054", "rs2907627", "rs1380109", "rs7024214", "rs7711972",
    "rs9658282", "rs11750720", "rs1793268", "rs774568", "rs6921786",
    "rs1699031", "rs6994771", "rs16926670", "rs465612", "rs3012084",
    "rs354850", "rs12803455", "rs13384873", "rs4364668", "rs8181047",
    "rs2179993", "rs12049335", "rs6079926", "rs2175144", "rs11564427",
    "rs7786389", "rs7005565", "rs17423335", "rs12474102", "rs191314",
    "rs10513168", "rs1711437", "rs1992620", "rs283115", "rs10754563",
    "rs10851727", "rs2173191", "rs7661353", "rs1342113", "rs7042073",
    "rs1567445", "rs10120375", "rs550060", "rs3761218", "rs4512977"
)
# OR
excludeFile <- system.file("extdata/Exclude/toyExclude.txt",
                           package = "snpEnrichment")

toyData_exclude <- excludeSNP(toyData, excludeFile, mc.cores = 1)

# Warning: compareEnrichment is in development!!
compareResults <- compareEnrichment(object.x = toyData,
                                    object.y = toyData_exclude,
                                    pattern = "Chrom",
                                    nSample = 10,
                                    empiricPvalue = TRUE,
                                    mc.cores = 1,
                                    onlyGenome = TRUE)


####################
### 5. Watch results
show(toyData)
print(toyData)
head(getEnrichSNP(toyData, type = "xSNP"))

show(toyData_exclude)
print(toyData_exclude)
head(getEnrichSNP(toyData_exclude, type = "eSNP"))