This procedure visualizes the phenotypic distribution linked to each of the
genetic states of a specific genotype.
Usage
plotSpecificGenotype(genotype, phenotype, index)
Arguments
genotype
Character matrix or data frame, containing SNPs/SAAPs as
columns or alternatively as a DNAMultipleAlignment/AAMultipleAlignment
Biostrings object.
phenotype
Numerical vector whose elements correspond to the
genotype.
index
Index (number) of the specific genotype column within the
genotype data which is to be plotted.
Details
This procedure allows the user to inspect a specific genotype with respect to
the the phenotype. It uses a boxplot notation to plot the phenotypes as a
function of the states of that genotype. The resulting boxplot will visualize
whether the different states of the specific genotype are linked to different
and disjoint phenotypic distributions, which is a signature of a strong
association between the genotype and the phenotype.
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.
You are welcome to redistribute it under certain conditions.
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/plotSpecificGenotype.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotSpecificGenotype
> ### Title: Visualizing specific genotypes
> ### Aliases: plotSpecificGenotype
>
> ### ** Examples
>
> #Example 1:
> data(genotype.snp) #or data(genotype.snp.msa)
> data(phenotype.snp)
> specific.genotype.plot <- plotSpecificGenotype(genotype = genotype.snp,
+ phenotype = phenotype.snp, index = 1)
>
> #Example 2:
> data(genotype.saap) #or ata(genotype.saap.msa)
> data(phenotype.saap)
> specific.genotype.plot <- plotSpecificGenotype(genotype = genotype.saap,
+ phenotype = phenotype.saap, index = 3)
>
>
>
>
>
> dev.off()
null device
1
>