an SCESet object containing expression values and
experimental information. Must have been appropriately prepared.
col_by_variable
variable name (must be a column name of pData(object))
to be used to assign colours to cell-level values.
n
numeric scalar giving the number of the most expressed features to
show. Default value is 50.
drop_features
a character, logical or numeric vector indicating which
features (e.g. genes, transcripts) to drop when producing the plot. For
example, control genes might be dropped to focus attention on contribution
from endogenous rather than synthetic genes.
exprs_values
which slot of the assayData in the object
should be used to define expression? Valid options are "counts" (default),
"tpm", "fpkm" and "exprs".
Details
Plot the percentage of counts accounted for by the top n most highly
expressed features across the dataset.
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/plotHighestExprs.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotHighestExprs
> ### Title: Plot the features with the highest expression values
> ### Aliases: plotHighestExprs
>
> ### ** Examples
>
> data("sc_example_counts")
> data("sc_example_cell_info")
> pd <- new("AnnotatedDataFrame", data = sc_example_cell_info)
> rownames(pd) <- pd$Cell
> example_sceset <- newSCESet(countData = sc_example_counts, phenoData = pd)
> example_sceset <- calculateQCMetrics(example_sceset, feature_controls = 1:500)
> plotHighestExprs(example_sceset, col_by_variable="total_features")
> plotHighestExprs(example_sceset, col_by_variable="Mutation_Status")
>
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.
