snpEnrichment (version 1.2-3)

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 (>= 2.15.0), methods, parallel URL: http://www-good.ibl.fr/ Encoding: UTF-8 }

See Also

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

Examples

#######################
### 1. Data Preparation
snpInfoDir <- system.file("extdata/snpInfo", 
                          package = "snpEnrichment")
snpListDir <- system.file("extdata/List", 
                          package = "snpEnrichment")
signalFile <- system.file("extdata/Signal/toySignal.txt", 
                          package = "snpEnrichment")
initFiles(pattern = "Chrom", snpInfoDir, snpListDir, 
          signalFile, mc.cores = 1)
writeLD(pattern = "Chrom", snpInfoDir, signalFile, ldDir = NULL, 
        ldThresh = 0.8, mc.cores = 1)

###################
### 2. Reading data
snpListDir <- system.file("extdata/List", 
                          package = "snpEnrichment")
signalFile <- system.file("extdata/Signal/toySignal.txt", 
                          package = "snpEnrichment")
excludeFile <- system.file("extdata/Exclude/toyExclude.txt", 
                           package = "snpEnrichment")
snpInfoDir <- system.file("extdata/snpInfo", 
                          package = "snpEnrichment")
data(transcript)
transcriptFile <- transcript

toy_M1 <- readEnrichment(pattern = "Chrom", signalFile, 
                         transcriptFile, snpListDir, 
                         snpInfoDir, distThresh = 1000, 
                         sigThresh = 0.05, LD = "FALSE", 
                         ldDir = NULL, extendMethod = "ld", 
                         mc.cores = 1)
toy_M1


########################
### 3. Computing results
data(toyEnrichmentM1)
reSample(object = toyEnrichmentM1, 
         nSample = 10, 
         MAFpool = c(0.05, 0.10, 0.2, 0.3, 0.4, 0.5), 
         mc.cores = 1,
         onlyGenome = FALSE)


#######################
### 5. Further analysis
## Exclude SNP from original list.
data(toyEnrichmentM1) # data(toyEnrichmentM2)
excludeFile <- c(
    "rs7897180", "rs4725479", "rs315404", "rs17390391", "rs1650670",
    "rs6783390", "rs1642009", "rs4756586", "rs11995037", "rs4977345",
    "rs13136448", "rs4233536", "rs11151079", "rs2299657", "rs4833930",
    "rs1384", "rs7168184", "rs6909895", "rs7972667", "rs2293229",
    "rs918216", "rs6040608", "rs2817715", "rs13233541", "rs4486743",
    "rs2127806", "rs10912854", "rs1869052", "rs9853549", "rs448658",
    "rs2451583", "rs17483288", "rs10962314", "rs9612059", "rs1384182",
    "rs8049208", "rs12215176", "rs2980996", "rs1736976", "rs8089268",
    "rs10832329", "rs12446540", "rs7676237", "rs869922", "rs16823426",
    "rs1374393", "rs13268781", "rs11134505", "rs7325241", "rs7520109"
)

toyM1_exclude <- excludeSNP(toyEnrichmentM1, excludeFile, mc.cores = 1)

compareResults <- compareEnrichment(object.x = toyEnrichmentM1, 
                                    object.y = toyM1_exclude, 
                                    pattern = "Chrom", 
                                    nSample = 10, 
                                    mc.cores = 1, 
                                    onlyGenome = TRUE)


####################
### 4. Watch results
show(toyEnrichmentM1)
summary(toyEnrichmentM1)

show(toyM1_exclude)
summary(toyM1_exclude)