plotVolcano {OUTRIDER}R Documentation

Visualization functions for OUTRIDER

Description

The OUTRIDER package provides mutliple functions to visualize the data and the results of a full data set analysis.

This is the list of all plotting function provided by OUTRIDER:

For a detailed description of each plot function please see the details. Most of the functions share the same parameters.

Usage

plotVolcano(ods, sampleID, main, padjCutoff = 0.05, zScoreCutoff = 0,
  pch = 16, basePlot = FALSE, col = c("gray", "firebrick"))

plotQQ(ods, geneID, main, global = FALSE, padjCutoff = 0.05,
  zScoreCutoff = 0, samplePoints = TRUE, legendPos = "topleft",
  outlierRatio = 0.001, conf.alpha = 0.05, pch = 16, xlim = NULL,
  ylim = NULL, col = NULL)

plotExpressionRank(ods, geneID, main, padjCutoff = 0.05,
  zScoreCutoff = 0, normalized = TRUE, basePlot = FALSE,
  log = TRUE, col = c("gray", "firebrick"), ...)

plotCountCorHeatmap(ods, normalized = TRUE, rowCentered = TRUE,
  rowCoFactor = NULL, rowColSet = "Set1", colCoFactor = NULL,
  colColSet = "Set2", nCluster = 4,
  main = "Count correlation heatmap", dendrogram = "both",
  basePlot = TRUE, names = c("both", "row", "col", "none"), ...)

plotAberrantPerSample(ods, main, padjCutoff = 0.05, zScoreCutoff = 0,
  outlierRatio = 0.001, col = brewer.pal(3, "Dark2")[c(1, 2)],
  yadjust = c(1.2, 1.2), labLine = c(3.5, 3),
  ylab = "#Aberrantly expressed genes", labCex = par()$cex,
  ymax = NULL, ...)

plotFPKM(ods)

## S4 method for signature 'OutriderDataSet'
plotDispEsts(object, compareDisp, xlim, ylim,
  main = "Dispersion estimates versus mean expression", ...)

plotPowerAnalysis(ods)

plotEncDimSearch(ods)

Arguments

ods, object

An OutriderDataSet object.

sampleID, geneID

A sample or gene ID, which should be plotted. Can also be a vector. Integers are treated as indices.

main

Title for the plot, if missing a default title will be used.

padjCutoff, zScoreCutoff

Significance or Z-score cutoff to mark outliers

pch

Integer or character to be used for plotting the points

basePlot

if TRUE, use the R base plot version, else use the plotly framework, which is the default

col

Set color for the points. If set, it must be a character vector of length 2. (1. normal point; 2. outlier point)

global

Flag to plot a global Q-Q plot, default FALSE

samplePoints

Sample points for Q-Q plot, defaults to max 30k points

legendPos

Set legendpos, by default topleft.

outlierRatio

The fraction to be used for the outlier sample filtering

conf.alpha

If set, a confidence interval is plotted, defaults to 0.05

xlim, ylim

The x/y limits for the plot or NULL to use the full data range

normalized

If TRUE, the normalized counts are used, the default, otherwise the raw counts

log

If TRUE, the default, counts are plotted in log10.

...

Additional parameters passed to plot() or plot_ly() if not stated otherwise in the details for each plot function

rowCentered

If TRUE, the counts are row-wise (gene-wise) centered

rowCoFactor

A vector of co-factors for color coding the rows

rowColSet

A vector of colors or a color set from RColorBrewer

colCoFactor

A vector of co-factors for color coding the columns

colColSet

A vector of colors or a color set from RColorBrewer

nCluster

An integer to be used for cutting the dendrogram into groups. If this argument is set the resulting clusters are saved in the returned OutriderDataSet.

dendrogram

A character string indicating whether to draw 'none', 'row', 'column' or 'both' dendrograms.

names

character string indicating whether to draw 'none', 'row', 'col', or 'both' names.

yadjust

Option to adjust position of Median and 90 percentile labels.

labLine

Option to move axis labels

ylab

The y axis label

labCex

The label cex parameter

ymax

If set, ymax is the upper bound for the plot range on the y axis.

compareDisp

If TRUE, the default, and if the autoCorrect normalization was used it computes the dispersion without autoCorrect and plots it for comparison.

Details

plotAberrantPerSample: The number of aberrant events per sample are plotted sorted by rank. The ... parameters are passed on to the aberrant function.

plotVolcano: the volcano plot is sample-centric. It plots for a given sample the negative log10 nominal P-values against the Z-scores for all genes.

plotExpressionRank: This function plots for a given gene the expression level against the expression rank for all samples. This can be used with normalized and unnormalized expression values.

plotQQ: the quantile-quantile plot for a given gene or if global is set to TRUE over the full data set. Here the observed P-values are plotted against the expected ones in the negative log10 space.

plotCountCorHeatmap: The correlation heatmap of the count data of the full data set. Default the values are log transformed and row centered. This function returns an OutriderDataSet with annotated clusters if requested. The ... arguments are passed to the heatmap.2 function.

plotFPKM: The distribution of FPKM values. If the OutriderDataSet object contains the passedFilter column, it will plot both FPKM distributions for the expressed genes and for the filtered genes.

plotDispEsts: Plots the dispersion of the OutriderDataSet model against the normalized mean count. If autoCorrect is used it will also estimate the dispersion without normalization for comparison.

plotPowerAnalysis: The power analysis plot should give the user a ruff estimate of the events one can be detected with OUTRIDER. Based on the dispersion of the provided OUTRIDER data set the theoretical P-value over the mean expression is plotted. This is done for different expression levels. The curves are smooths to make the reading of the plot easier.

Value

If base R graphics are used nothing is returned else the plotly or the gplot object is returned.

Examples

ods <- makeExampleOutriderDataSet(dataset="Kremer")
implementation <- 'autoencoder'

ods <- filterExpression(ods, minCounts=TRUE)
ods <- OUTRIDER(ods, implementation=implementation)

plotAberrantPerSample(ods)

plotVolcano(ods, 1)
plotVolcano(ods, 'MUC1404', basePlot=TRUE)

plotExpressionRank(ods, 1)
plotExpressionRank(ods, "FAAH", normalized=FALSE, 
    log=FALSE, main="Over expression outlier", basePlot=TRUE)

plotQQ(ods, 1)
plotQQ(ods, global=TRUE, outlierRatio=0.001)

sex <- sample(c("female", "male"), dim(ods)[2], replace=TRUE)
colData(ods)$sex <- sex
ods <- plotCountCorHeatmap(ods, colCoFactor="sex", normalized=FALSE)
ods <- plotCountCorHeatmap(ods, nCluster=4)
head(colData(ods)$clusterNumber)

mcols(ods)$basepairs <- 1
mcols(ods)$passedFilter <- rowMeans(counts(ods)) > 10
plotFPKM(ods)

plotDispEsts(ods, compareDisp=FALSE)

plotPowerAnalysis(ods)

## Not run: 
ods <- findEncodingDim(ods)
plotEncDimSearch(ods)

## End(Not run)


[Package OUTRIDER version 1.0.4 Index]