volcanoPlot: Volcano plot of fold changes/differences against p-values

In tnaake/MatrixQCvis: Shiny-based interactive data-quality exploration for omics data

Volcano plot of fold changes/differences against p-values

Description

The function ComplexHeatmap creates a volcano plot. On the y-axis the -log10(p-values) are displayed, while on the x-axis the fold changes/differences are displayed. The output of the function differs depending on the type parameter. For type == "ttest", the fold changes are plotted; for type == "proDA", the differences are plotted.

Usage

volcanoPlot(df, type = c("ttest", "proDA"))

Arguments

df	data.frame as received from topTable (ttest) or test_diff (proDA)
type	character

Details

Internal use in shinyQC.

Value

plotly

Examples

## create se
a <- matrix(seq_len(100), nrow = 10, ncol = 10, 
            dimnames = list(seq_len(10), paste("sample", seq_len(10))))
a[c(1, 5, 8), seq_len(5)] <- NA
set.seed(1)
a <- a + rnorm(100)
a_i <- imputeAssay(a, method = "MinDet")
cD <- data.frame(sample = colnames(a), 
    type = c(rep("1", 5), rep("2", 5)))
rD <- data.frame(spectra = rownames(a))
se <- SummarizedExperiment::SummarizedExperiment(assay = a, 
                                rowData = rD, colData = cD)
se_i <- SummarizedExperiment::SummarizedExperiment(assay = a_i, 
                                rowData = rD, colData = cD)

## create model and contrast matrix
modelMatrix_expr <- stats::formula("~ 0 + type")
contrast_expr <- "type1-type2"
modelMatrix <- model.matrix(modelMatrix_expr, data = colData(se))
contrastMatrix <- limma::makeContrasts(contrasts = contrast_expr, 
                                levels = modelMatrix)

## ttest
fit <- limma::lmFit(a_i, design = modelMatrix)
fit <- limma::contrasts.fit(fit, contrastMatrix)
fit <- limma::eBayes(fit, trend = TRUE)
df_ttest <- limma::topTable(fit, n = Inf, adjust = "fdr", p = 0.05)
df_ttest <- cbind(name = rownames(df_ttest), df_ttest)

## plot
volcanoPlot(df_ttest, type = "ttest")

## proDA

fit <- proDA::proDA(a, design = modelMatrix)
df_proDA <- proDA::test_diff(fit = fit, contrast = contrast_expr,
        sort_by = "adj_pval")

## plot
volcanoPlot(df_proDA, type = "proDA")

tnaake/MatrixQCvis documentation built on June 20, 2024, 7:22 a.m.