Show labels on plot_mva

[mavino]

Is there any possibility to show the sample labels when running plot_mva()?

I was able to do that by catching some of the code inside function plot_mva() as follows

    ret <- .get_mds_matrix(mvaresults, components, color_by)
    mds_matrix <- ret$mds_matrix
    color_by <- ret$color_by
    cols <- colnames(mds_matrix)
ggplot(mds_matrix, aes_string(cols[[2]], cols[[3]], 
        label = "Sample", color = color_by)) + geom_point(size = 3, 
        pch = 16) + geom_text(vjust = -0.5, size = 3, color = "black")

so this piece of code shows my labels but the plot is not nice as running:

plot_mva(mvaresults, color_by="Age", components = c(1,2))

Thank you so much.

[ahmohamed]

Hi @mavino, Sorry for the late response. One of the design principles that I tried to stick with in developing lipidr is ti reuse existing R objects (where possible) to facilitate integration with the rest of the eco system. All plot functions readily return a ggplot object that you can modify and extend as you wish. So, it's very easy to add text labels to a static plot using the code below. We also support showing the sample labels in interactive plots.

library(lipidr)
#> Loading required package: SummarizedExperiment
#> Loading required package: MatrixGenerics
#> Loading required package: matrixStats
#> 
#> Attaching package: 'MatrixGenerics'
#> The following objects are masked from 'package:matrixStats':
#> 
#>     colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
#>     colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
#>     colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
#>     colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
#>     colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
#>     colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
#>     colWeightedMeans, colWeightedMedians, colWeightedSds,
#>     colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
#>     rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
#>     rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
#>     rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
#>     rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
#>     rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
#>     rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
#>     rowWeightedSds, rowWeightedVars
#> Loading required package: GenomicRanges
#> Loading required package: stats4
#> Loading required package: BiocGenerics
#> 
#> Attaching package: 'BiocGenerics'
#> The following objects are masked from 'package:stats':
#> 
#>     IQR, mad, sd, var, xtabs
#> The following objects are masked from 'package:base':
#> 
#>     anyDuplicated, aperm, append, as.data.frame, basename, cbind,
#>     colnames, dirname, do.call, duplicated, eval, evalq, Filter, Find,
#>     get, grep, grepl, intersect, is.unsorted, lapply, Map, mapply,
#>     match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,
#>     Position, rank, rbind, Reduce, rownames, sapply, setdiff, sort,
#>     table, tapply, union, unique, unsplit, which.max, which.min
#> Loading required package: S4Vectors
#> 
#> Attaching package: 'S4Vectors'
#> The following objects are masked from 'package:base':
#> 
#>     expand.grid, I, unname
#> Loading required package: IRanges
#> Loading required package: GenomeInfoDb
#> 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")'.
#> 
#> Attaching package: 'Biobase'
#> The following object is masked from 'package:MatrixGenerics':
#> 
#>     rowMedians
#> The following objects are masked from 'package:matrixStats':
#> 
#>     anyMissing, rowMedians
library(ggplot2)
data(data_normalized)

mvaresults <- mva(data_normalized, measure = "Area", method = "PCA")
plot_mva(mvaresults, color_by = "group") + geom_text(vjust = -0.5, size = 3, color = "black")
#> Warning: The following aesthetics were dropped during statistical transformation: label
#> ℹ This can happen when ggplot fails to infer the correct grouping structure in
#>   the data.
#> ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
#>   variable into a factor?

^{Created on 2023-05-07 with reprex v2.0.2}