The MsDataHub package uses the ExperimentHub infrastructure to distribute raw mass spectrometry data files, peptide spectrum matches or quantitative data from proteomics and metabolomics experiments.
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The MsDataHub package uses the ExperimentHub infrastructure to distribute raw mass spectrometry data files, peptide spectrum matches or quantitative data from proteomics and metabolomics experiments.
library(MsDataHub)
library(Spectra)
library(QFeatures)
# 1. Load raw MS data (TripleTOF DDA) and create a Spectra object
f_dda <- PestMix1_DDA.mzML()
s_dda <- Spectra(f_dda)
# 2. Load DIA-NN label-free DIA data and read into QFeatures
lfdia <- read.delim(MsDataHub::benchmarkingDIA.tsv())
qf <- readQFeaturesFromDIANN(lfdia)
Note: Inputs are cached file paths retrieved from MsDataHub accessor functions; outputs are Spectra or QFeatures objects containing mass spectrometry data.
.mzML, .CDF) from standard proteomics/metabolomics experiments via ExperimentHub caching..mzid) using PSM() from the PSMatch package.SummarizedExperiment or QFeatures structures using readSummarizedExperiment() or readQFeaturesFromDIANN().xcms because MsDataHub only distributes pre-existing example datasets.MSstats because MsDataHub is a data repository rather than an analytical tool.AnnotationDbi or biomaRt because MsDataHub only provides mass spectrometry-specific data and contaminant databases..mzML (e.g., PestMix1_DDA.mzML()), .CDF (e.g., ko15.CDF()), or compressed .mzML.gz..mzid format (e.g., TMT_Erwinia_1uLSike_Top10HCD_isol2_45stepped_60min_01.20141210.mzid()).cptac_peptides.txt(), benchmarkingDIA.tsv()) containing peptide intensities or DIA-NN report outputs.readQFeaturesFromDIANN(), set to "mTRAQ" for multiplexed plexDIA data.readSummarizedExperiment(), specifies the field separator character for reading text files.readSummarizedExperiment(), specifies the column indices containing quantitative intensity data.MsDataHub() inside DT::datatable() to browse the complete list of available datasets and their metadata.Spectra object using Spectra(f) to leverage memory-efficient backends.read.delim() to load the file path returned by MsDataHub::benchmarkingDIA.tsv() before passing it to readQFeaturesFromDIANN().PestMix1_DDA.mzML()) to download and retrieve the local cache path first.grep("Intensity\\.", names(read.delim(f))) to dynamically identify quantitative columns before calling readSummarizedExperiment().multiplexing is omitted or set correctly when using readQFeaturesFromDIANN() on label-free vs mTRAQ plexDIA data.No reviews yet. Tell others what you thought.
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