tmzmlMaker: Maker of tmzML documents

In RaMS: R Access to Mass-Spec Data

Maker of tmzML documents

Description

This function converts mzML and mzXML documents into "transposed" mzML (tmzML) documents. Traditional mass-spec data is organized by scan number, corresponding to retention time, but this isn't always the most sensible format. Often, it makes more sense to organize a mass-spec file by m/z ratio instead. This allows parsers to scan and decode a much smaller portion of the file when searching for a specific mass, as opposed to the traditional format which requires that every scan be opened, searched, and subset. The tmzML document implements this strategy and allows the creation of MS object representations that use essentially zero memory because the data is read off the disk instead of being stored in RAM. RaMS has been designed to interface with these new file types identically to traditional files, allowing all your favorite tidyverse tricks to work just as well and much more quickly.

Usage

tmzmlMaker(input_filename, output_filename = NULL, verbosity = 0, binwidth = 3)

Arguments

input_filename	Character vector of length 1 with the name of the file to be converted. Can only handle mzML and mzXML currently - other formats should be converted to one of these first, using (for example) Proteowizard's msconvert tool.
output_filename	The name of the file that will be written out. Should end in ".tmzML" and will throw a warning otherwise. Often, it makes sense to have two folders in a working directory, one containing the original mzML files and a second, parallel folder for the tmzMLs.
verbosity	Numeric value between 0 and 2, corresponding to level of verbosity shared by the function as it proceeds. 0 means no output, 1 will produce mile markers after file opening, MS1 and MS2 conversion, and 2 will provide progress bars between each mile marker.
binwidth	Numeric value controlling the width of the bins in m/z space to create. Because MS data is created in such a way that m/z values are continuous, they must be binned together to create a discrete representation that can be searched efficiently. Lower values (0.1-1) will have faster retrieval times, while higher values (5-10) will have faster conversion times.

Value

An msdata_connection object. This object behaves exactly like a normal RaMS list with values for MS1, MS2, etc. but secretly just contains pointers to the files requested because the data is extracted on the fly. The S3 msdata_connection object is necessary to create new behaviors for '$' and '[' that allow indexing like normal.

Examples

## Not run: 
sample_dir <- system.file("extdata", package = "RaMS")
sample_files <- list.files(sample_dir, full.names=TRUE, pattern="LB.*mzML")
tmzml_filenames <- gsub(x=sample_files, "\\.mzML.gz", ".tmzML")

# Convert a single file
tmzmlMaker(sample_files[1], tmzml_filenames[1])
file_data <- grabMSdata(tmzml_filenames[1], grab_what="everything", verbosity=2)
file_data$MS1[mz%between%pmppm(118.0865)]

# Multiple files
mapply(tmzmlMaker, sample_files, tmzml_filenames)
file_data <- grabMSdata(tmzml_filenames, grab_what="everything", verbosity=2)
betaine_data <- file_data$MS1[mz%between%pmppm(118.0865)]

# Plot output
plot(betaine_data$rt, betaine_data$int, type="l")
library(ggplot2)
ggplot(betaine_data) + geom_line(aes(x=rt, y=int, color=filename))

# Clean up afterward
file.remove(tmzml_filenames)

## End(Not run)

RaMS documentation built on Dec. 28, 2022, 2:26 a.m.