Plot components from isoPLSDA analysis (pairs plot)

Description

Plot the most significant components that come from isoPLSDA analysis together with the density of the samples scores along those components.

Usage

isoPLSDAplot(pls)

Arguments

Details

The function isoPLSDAplot helps to visualize the results from isoPLSDA. It will plot the samples using the significant components (t1, t2, t3 ...) from the PLS-DA analysis and the samples score distribution along the components. It uses ggpairs for the plot.

Value

ggpairs plot showing the scores for each sample using isomiRs/miRNAs expression to explain variation.

data.frame object with a first column refering to the sample group, and the following columns refering to the score that each sample has for each component from the PLS-DA analysis.

Examples

data(mirData)
# Only miRNAs with > 10 reads in all samples.
ids <- isoCounts(mirData, minc=10, mins=6)
ids <- isoNorm(ids)
pls.ids <- isoPLSDA(ids, "condition", nperm = 2)
isoPLSDAplot(pls.ids)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(isomiRs)
Loading required package: DiscriMiner
Loading required package: IRanges
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 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: GenomicRanges
Loading required package: GenomeInfoDb
Loading required package: SummarizedExperiment
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/isomiRs/isoPLSDAplot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: isoPLSDAplot
> ### Title: Plot components from isoPLSDA analysis (pairs plot)
> ### Aliases: isoPLSDAplot
> 
> ### ** Examples
> 
> data(mirData)
> # Only miRNAs with > 10 reads in all samples.
> ids <- isoCounts(mirData, minc=10, mins=6)
> ids <- isoNorm(ids)
converting counts to integer mode
-- note: fitType='parametric', but the dispersion trend was not well captured by the
   function: y = a/x + b, and a local regression fit was automatically substituted.
   specify fitType='local' or 'mean' to avoid this message next time.
> pls.ids <- isoPLSDA(ids, "condition", nperm = 2)
> isoPLSDAplot(pls.ids)
    condition         t1         t2        t3
nb1        nb  16.685809 -12.841132  2.490488
nb2        nb   3.040456  15.827478  5.625597
nb3        nb   9.342125   7.150871 -7.018976
o1          o  -9.240669  -2.075327 -3.915473
o2          o  -9.706194  -3.463364 -1.790136
o3          o -10.121527  -4.598526  4.608499
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>