Visualizing GWAS results

Description

This procedure plots the results obtained using runGenphenSnp or runGenphenSaap.

Usage

plotGenphenResults(genphen.results)

Arguments

Details

This procedure plots the results obtained using runGenphenSnp or runGenphenSaap. Each result entry is plotted as a point with respect to its effect size and classification accuracy attributes, whereby the color of the points is directly proportional to the classification accuracy. The region in the top-right corner of the plot is where the genotypes which have the strongest association with the phenotype are found.

Value

Author(s)

Simo Kitanovski <simo.kitanovski@uni-due.de>

See Also

runGenphenSaap, runGenphenSnp, plotGenphenResults, plotSpecificGenotype

Examples

#Example 1:
data(genotype.snp)
#or data(genotype.snp.msa) in this case you cannot subset genotype.snp[, 1:5]
data(phenotype.snp)
genphen.results <- runGenphenSnp(genotype = genotype.snp[, 1:5],
phenotype = phenotype.snp, technique = "svm", fold.cv = 0.66, boots = 100)
genphen.plot <- plotGenphenResults(genphen.results = genphen.results)

#Example 2:
data(genotype.saap)
#or data(genotype.saap.msa) in this case you cannot subset genotype.saap[, 1:5]
data(phenotype.saap)
genphen.results <- runGenphenSaap(genotype = genotype.saap[, 1:5],
phenotype = phenotype.saap, technique = "svm", fold.cv = 0.66, boots = 100)
genphen.plot <- plotGenphenResults(genphen.results = genphen.results)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(genphen)
Loading required package: randomForest
randomForest 4.6-12
Type rfNews() to see new features/changes/bug fixes.
Loading required package: e1071
Loading required package: ggplot2

Attaching package: 'ggplot2'

The following object is masked from 'package:randomForest':

    margin

Loading required package: effsize
Loading required package: Biostrings
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following object is masked from 'package:randomForest':

    combine

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: XVector
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/genphen/plotGenphenResults.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotGenphenResults
> ### Title: Visualizing GWAS results
> ### Aliases: plotGenphenResults
> 
> ### ** Examples
> 
> #Example 1:
> data(genotype.snp)
> #or data(genotype.snp.msa) in this case you cannot subset genotype.snp[, 1:5]
> data(phenotype.snp)
> genphen.results <- runGenphenSnp(genotype = genotype.snp[, 1:5],
+ phenotype = phenotype.snp, technique = "svm", fold.cv = 0.66, boots = 100)
> genphen.plot <- plotGenphenResults(genphen.results = genphen.results)
Warning messages:
1: Removed 1 rows containing missing values (geom_point). 
2: Removed 1 rows containing missing values (geom_point). 
> 
> #Example 2:
> data(genotype.saap)
> #or data(genotype.saap.msa) in this case you cannot subset genotype.saap[, 1:5]
> data(phenotype.saap)
> genphen.results <- runGenphenSaap(genotype = genotype.saap[, 1:5],
+ phenotype = phenotype.saap, technique = "svm", fold.cv = 0.66, boots = 100)
> genphen.plot <- plotGenphenResults(genphen.results = genphen.results)
Warning messages:
1: Removed 14 rows containing missing values (geom_point). 
2: Removed 14 rows containing missing values (geom_point). 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>