multi_volcano_plots: multi_volcano_plots: directly converts MaxQuant output to...

In devradiumking/maxabpp: Visualization of MaxQuant output for activity-based protein profiling experiments

Description

multi_volcano_plots: directly converts MaxQuant output to multiple volcano plots

Usage

multi_volcano_plots(
  raw = read.delim("modificationSpecificPeptides.txt", header = TRUE, sep = "\t"),
  metadata = read.delim("metadata.txt", header = TRUE, sep = "\t"),
  name_probe_mod = c("Mod"),
  max_each_mod = 1,
  max_total_mods = 1,
  quantitation_level = "peptide",
  background_check = FALSE,
  normalize_to = NULL,
  xlim = c(-10, 3),
  ylim = c(0, 5),
  label_col_name = "Gene.Names",
  pCutoff = 0.05,
  FCcutoff = -2
)

Arguments

raw	a dataframe by reading modificationSpecificPeptides.txt
metadata	a dataframe that maches the MaxQuant input. Column 1: Intensity (such as Intensity samplename, same as the column names in modificationSpecificPeptides.txt) name Column 2: Replicate group (use the same name for each group of replicates)
name_probe_mod	a string vector of chemical probe/modification names, such as c("Mod1", "Mod2"), must match MaxQuant input
max_each_mod	a integer as the maximal number of modifications on a single peptide, set for each chemical probe
max_total_mods	a integer as the maximal number of modifications on a single peptide, set for all chemical probes Note max_each_mod must not be less than max_total_mods
quantitation_level	a string, must be either "peptide" or "protein"
background_check	a boolean, FALSE = quantify probe-modified peptides, TRUE = quantify non-probe-modified peptides
normalize_to	a string, must be either "sum_all", "mean_all", (normalize to all peptides) "sum_background", or "mean_background" (normalize to background/non-probe-modified peptides).
xlim	a integer vector, such as c(-5, 5) for an x axis range of -5 to 5
ylim	a integer vector, such as c(0, 5) for an y axis range of 0 to 5
label_col_name	the input column name for labeling volcano plot data points such as "Gene.Names"
pCutoff	the p-Value cutoff, for instance, default p-value = 0.05
FCcutoff	the fold change cutoff, Note for ABPP, we are only interested in negative fold change (Lower intensity at higher inhibitor concentration)

Value

volcano plots

See Also

pairwise_LFQ append_ec_sites plot_volcano

Examples

 multi_volcano_plots(raw = raw, metadata = metadata, name_probe_mod = c("Mod"),
                   max_each_mod = 1, max_total_mods = 1, quantitation_level = "peptide" , background_check = FALSE, normalize_to = "mean_all",
                   xlim = c(-10, 3), ylim = c(0, 5), label_col_name = "Gene.Names", pCutoff = 0.05, FCcutoff = -2)

devradiumking/maxabpp documentation built on May 31, 2020, 9:01 a.m.