analyze_unknown_mods {flowTraceR} | R Documentation |
Analysis of unknown modifications
Description
Analysis of the traceR_precursor_unknownMods or traceR_mod.peptides_unknownMods column
Usage
analyze_unknown_mods(
input_df,
level = c("precursor, modified_peptides"),
plot = TRUE,
plot_characteristic = c("absolute", "relative")
)
Arguments
input_df |
A tibble with the traceR_precursor_unknownMods or traceR_mod.peptides_unknownMods column. |
level |
Choose either |
plot |
Logical value, default is TRUE. If |
plot_characteristic |
If |
Details
Shows the absolute and relative counts of TRUE/FALSE of the traceR_precursor_unknownMods or traceR_mod.peptides_unknownMods column - as data frame or plot. Duplicate traceR_mod.peptides entries or traceR_precursor entries are removed, respectively.
Value
This function returns a plot - absolute/relative counts - or a data frame.
Author(s)
Oliver Kardell
Examples
# Load libraries
library(dplyr)
library(stringr)
library(ggplot2)
library(tibble)
# Generate data
data <- tibble::tibble(
"traceR_mod.peptides" = c("AACLLPK",
"ALTDM(UniMod:35)PQM(UniMod:35)R",
"ALTDM(DummyModification)PQMK",
"ALTDM(UniMod:35)PQM(UniMod:35)R",
"ALTDM(DummyModification)PQMK"),
"traceR_mod.peptides_unknownMods" = c(FALSE, FALSE, TRUE, FALSE, TRUE),
"traceR_precursor" = c("AACLLPK2",
"ALTDM(UniMod:35)PQM(UniMod:35)R2",
"ALTDM(DummyModification)PQMK3",
"ALTDM(UniMod:35)PQM(UniMod:35)R2",
"ALTDM(DummyModification)PQMK3"),
"traceR_precursor_unknownMods" = c(FALSE, FALSE, TRUE, FALSE, TRUE)
)
# Generate Report - precursor level
analyze_unknown_mods(
input_df = data,
level = "precursor",
plot = FALSE
)
# Generate relative Plot - peptide level
analyze_unknown_mods(
input_df = data,
level = "modified_peptides",
plot = TRUE,
plot_characteristic = "relative"
)