smoothMAplot: A function to produce MA-plots.

In ATpoint/diffanalyseR: Wrapper functions for common tasks related to analysis of NGS counts data

Description

The function takes average log2-expression as X.values and logFC as Y.values and then uses smoothScatter() to produce MA-plots. Due to smoothScatter() resulting pdfs are typically small which is the reason we use this function rather than plot() or anything similar. Optionally, if one provides values via P.values, data points whose P.values are below Sig.Thresh will be colored in Sig.Color.

Usage

smoothMAplot(
  X.value,
  Y.value,
  Y.limits = NULL,
  y.quantile.low = 0.001,
  y.quantile.top = 0.999,
  Plot.xlab = "baseMean",
  Plot.ylab = "logFC",
  Plot.title = NULL,
  Plot.title.size = 1,
  Plot.cexlab = 1.5,
  Plot.cexaxis = 1.5,
  Plot.ColorRamp = NULL,
  Points.cex = 0.2,
  use.loessFit = FALSE,
  use.loessFit.Color = "red",
  abline0 = TRUE,
  abline2 = NULL
)

Arguments

X.value	log2 average expression values
Y.value	log2 fold changes
Y.limits	the limits of the y-axis, e.g. like c(-2,2), if NULL then automatically determined based on quantiles to capture most data points while avoiding excessive axis limits due to outliers
Plot.xlab	x-axis label
Plot.ylab	y-axis label
Plot.title	title of the plot,
Plot.title.size	cexsize of title
Plot.cexlab	cex size of the axis labels
Plot.cexaxis	cex size of the axis marks
Plot.ColorRamp	a color ramp for the plot, by default use the standard from smoothScatter() so white to blue
Points.cex	cex size of the data points below the Sig.Thresh
use.loessFit	logical, whether to use loessFit for a fit between Yval and Xval
use.loessFit.Color	color of that abline
abline0	logical, whether to add a y=0 abline
abline2	a numeric value, if set then will plot a horizontal abline at +/- that value
P.values	optional p-values from differential analysis
Sig.Thresh	threshold to select significant data points based on P.values
Sig.Color	color to highlight significant data points, default is firebrick
Add.Legend	logical, whether to add a legend at topright position with a summary of the number of data points above and below Sig.Thresh and the smallest arithmetic (not log2) fold change that was still significant at the given p-value cutoff

Author(s)

Alexander Toenges

ATpoint/diffanalyseR documentation built on Oct. 8, 2021, 10:11 p.m.