numeric scalar indicating the number of principal
components to plot, starting from the first principal component. Default is
2. If ncomponents is 2, then a scatterplot of PC2 vs PC1 is produced.
If ncomponents is greater than 2, a pairs plots for the top components
is produced. NB: computing more than two components for t-SNE can become very
time consuming.
colour_by
character string defining the column of pData(object) to
be used as a factor by which to colour the points in the plot.
shape_by
character string defining the column of pData(object) to
be used as a factor by which to define the shape of the points in the plot.
size_by
character string defining the column of pData(object) to
be used as a factor by which to define the size of points in the plot.
return_SCESet
logical, should the function return an SCESet
object with principal component values for cells in the
reducedDimension slot. Default is FALSE, in which case a
ggplot object is returned.
draw_plot
logical, should the plot be drawn on the current graphics
device? Only used if return_SCESet is TRUE, otherwise the plot
is always produced.
theme_size
numeric scalar giving default font size for plotting theme
(default is 10).
legend
character, specifying how the legend(s) be shown? Default is
"auto", which hides legends that have only one level and shows others.
Alternatives are "all" (show all legends) or "none" (hide all legends).
Details
The function cmdscale is used internally to
compute the multidimensional scaling components to plot.
Value
If return_SCESet is TRUE, then the function returns an
SCESet object, otherwise it returns a ggplot object.
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(scater)
Loading required package: Biobase
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
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Loading required package: ggplot2
Attaching package: 'scater'
The following object is masked from 'package:stats':
filter
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/scater/plotMDS.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotMDS
> ### Title: Produce a multidimensional scaling plot for an SCESet object
> ### Aliases: plotMDS plotMDS,SCESet-method plotMDSSCESet
>
> ### ** Examples
>
> ## Set up an example SCESet
> data("sc_example_counts")
> data("sc_example_cell_info")
> pd <- new("AnnotatedDataFrame", data = sc_example_cell_info)
> example_sceset <- newSCESet(countData = sc_example_counts, phenoData = pd)
> drop_genes <- apply(exprs(example_sceset), 1, function(x) {var(x) == 0})
> example_sceset <- example_sceset[!drop_genes, ]
> example_sceset <- calculateQCMetrics(example_sceset)
>
> ## define cell-cell distances
> cellDist(example_sceset) <- as.matrix(dist(t(exprs(example_sceset))))
>
> ## Examples plotting
> plotMDS(example_sceset)
> plotMDS(example_sceset, colour_by = "Cell_Cycle")
> plotMDS(example_sceset, colour_by = "Cell_Cycle",
+ shape_by = "Treatment")
>
> ## define cell-cell distances differently
> cellDist(example_sceset) <- as.matrix(dist(t(counts(example_sceset)),
+ method = "canberra"))
> plotMDS(example_sceset, colour_by = "Cell_Cycle",
+ shape_by = "Treatment", size_by = "Mutation_Status")
Warning message:
Using size for a discrete variable is not advised.
>
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.
