Last data update: 2014.03.03

R: Plot feature (gene) data from an SCESet object
plotFeatureDataR Documentation

Plot feature (gene) data from an SCESet object

Description

Plot feature (gene) data from an SCESet object

Usage

plotFeatureData(object, aesth = aes_string(x = "n_cells_exprs", y =
  "prop_total_counts"), theme_size = 10, ...)

Arguments

object

an SCESet object containing expression values and experimental information. Must have been appropriately prepared.

aesth

aesthetics function call to pass to ggplot. This function expects at least x and y variables to be supplied. The default is to produce a density plot of number of cells expressing the feature (requires calculateQCMetrics to have been run on the SCESet object prior).

theme_size

numeric scalar giving default font size for plotting theme (default is 10).

...

arguments passed to plotMetadata.

Details

Plot feature (gene) data from an SCESet object. If one variable is supplied then a density plot will be returned. If both variables are continuous (numeric) then a scatter plot will be returned. If one variable is discrete and one continuous then a violin plot with jittered points overlaid will be returned. If both variables are discrete then a jitter plot will be produced. The object returned is a ggplot object, so further layers and plotting options (titles, facets, themes etc) can be added.

Value

a ggplot plot object

Examples

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)
example_sceset <- calculateQCMetrics(example_sceset)
plotFeatureData(example_sceset, aesth=aes(x=n_cells_exprs, y=pct_total_counts))

Results


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/plotFeatureData.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotFeatureData
> ### Title: Plot feature (gene) data from an SCESet object
> ### Aliases: plotFeatureData
> 
> ### ** Examples
> 
> 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)
> example_sceset <- calculateQCMetrics(example_sceset)
> plotFeatureData(example_sceset, aesth=aes(x=n_cells_exprs, y=pct_total_counts))
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>