# Volcano Plots Produce volcano plot(s) of the given effect size and p values. ```r volcano(x, ...) ## Default S3 method: volcano(x, pval, effect0 = 0, sig.level = 0.05, effect.low = NULL, effect.high = NULL, color.low = "#4575B4", color.high = "#D73027", xlab = "effect size", ylab = "-log10(p value)", title = "Volcano Plot", alpha = 1, shape = 19, na.rm = TRUE, ...) ``` ## Arguments - `x`: in case of default method: measure of effect size. - `pval`: numeric, (adjusted) p values. - `effect0`: single numeric, value for no effect. - `sig.level`: single numeric, significance level. - `effect.low`: `NULL` or single numeric, boundary for low effect sizes. - `effect.high`: `NULL` or single numeric, boundary for low effect sizes. - `color.low`: color used if effect size smaller than `effect.low` and (adjusted) p value smaller than `sig.level`. - `color.high`: color used if effect size larger than `effect.high` and (adjusted) p value smaller than `sig.level`. - `xlab`: label of x-axis. - `ylab`: label of y-axis. - `title`: title of plot. - `alpha`: blending factor (default: no blending. - `shape`: point shape used. - `na.rm`: single logical, remove `NA` values before plotting. - ``...``: further arguments that may be passed through. ## Details The plot generates a `ggplot2` object that is shown. ## Returns Object of class `gg` and `ggplot`. ## References Wikipedia contributors, **Volcano plot (statistics)**, Wikipedia, The Free Encyclopedia, [https://en.wikipedia.org/w/index.php?title=Volcano_plot_(statistics)&oldid=900217316](https://en.wikipedia.org/w/index.php?title=Volcano_plot_(statistics)&oldid=900217316) (accessed December 25, 2019). For more sophisticated and flexible volcano plots see for instance: Blighe K, Rana S, Lewis M (2019). EnhancedVolcano: Publication-ready volcano plots with enhanced colouring and labeling. R/Bioconductor package. [https://github.com/kevinblighe/EnhancedVolcano](https://github.com/kevinblighe/EnhancedVolcano). ## Author(s) Matthias Kohl Matthias.Kohl@stamats.de ## Examples ```r ## Generate some data x <- matrix(rnorm(1000, mean = 10), nrow = 10) g1 <- rep("control", 10) y1 <- matrix(rnorm(500, mean = 11.75), nrow = 10) y2 <- matrix(rnorm(500, mean = 9.75, sd = 3), nrow = 10) g2 <- rep("treatment", 10) group <- factor(c(g1, g2)) Data <- rbind(x, cbind(y1, y2)) pvals <- apply(Data, 2, function(x, group) hsu.t.test(x ~ group)$p.value, group = group) ## compute log-fold change logfc <- function(x, group){ res <- tapply(x, group, mean) log2(res[1]/res[2]) } lfcs <- apply(Data, 2, logfc, group = group) volcano(lfcs, pvals, xlab = "log-fold change") volcano(lfcs, pvals, effect.low = -0.25, effect.high = 0.25, xlab = "log-fold change") volcano(lfcs, p.adjust(pvals, method = "fdr"), effect.low = -0.25, effect.high = 0.25, xlab = "log-fold change", ylab = "-log10(adj. p value)") volcano(2^lfcs, pvals, effect0 = 1, effect.low = 1/2^0.25, effect.high = 2^0.25, xlab = "mean difference") ```

volcano function