confects_plot_me2: Mean-expression vs effect size plot (version 2)

In pfh/topconfects: Top Confident Effect Sizes

Mean-expression vs effect size plot (version 2)

Description

Like plotMD in limma, plots effect size against mean expression level. Confect values are indicated using color. This may be useful for assessing whether effects are only being detected in highly expressed genes.

Usage

confects_plot_me2(confects, breaks = NULL, signed_colors = TRUE)

Arguments

confects	A "Topconfects" class object, as returned from limma_confects, edger_confects, or deseq2_confects.
breaks	A vector of non-negative confect thresholds to color points with. Chooses a sensible set of breaks if none are given.
signed_colors	Should positive and negative confects be colored distinctly, red and blue.

Value

A ggplot2 object. Working non-interactively, you must print() this for it to be displayed.

Examples

library(NBPSeq)
library(edgeR)
library(limma)

data(arab)

# Extract experimental design from sample names
treat <- factor(substring(colnames(arab),1,4), levels=c("mock","hrcc"))
time <- factor(substring(colnames(arab),5,5))

# Keep genes with at least 3 samples having an RPM of more than 2
y <- DGEList(arab)
keep <- rowSums(cpm(y)>2) >= 3
y <- y[keep,,keep.lib.sizes=FALSE]
y <- calcNormFactors(y)

# Find top confident fold changes by topconfects-limma-voom method
design <- model.matrix(~time+treat)
voomed <- voom(y, design)
fit <- lmFit(voomed, design)
confects <- limma_confects(fit, "treathrcc")

# Plot confident effect size against mean expression
# (estimated effect size also shown as grey dots)
confects_plot_me2(confects)

pfh/topconfects documentation built on Dec. 12, 2024, 10:19 p.m.