Like plotMD in limma, plots effect size against mean expression level. However shows "confect" on the y axis rather than "effect" ("effect" is shown underneath in grey). This may be useful for assessing whether effects are only being detected only in highly expressed genes.

confects_plot_me(confects)

Arguments

confects

A "Topconfects" class object, as returned from limma_confects, edger_confects, or deseq2_confects.

Value

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

Examples

library(NBPSeq) library(edgeR)
#> Loading required package: limma
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_me(confects)