Isobaric labeling update in MaxQuant

Published: 1 October 2024| Version 1 | DOI: 10.17632/s3gfmcbghm.1
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Description

We present an update of the MaxQuant software for isobaric labeling data and evaluate its performance on benchmark datasets. Impurity correction factors can be applied to labels mixing C- and N-type reporter ions, such as TMT Pro. Application to a single-cell species mixture benchmark shows high accuracy of the impurity-corrected results. TMT data recorded with FAIMS separation can be analyzed directly in MaxQuant without splitting the raw data into separate files per FAIMS voltage. Weighted median normalization, is applied to several datasets, including large-scale human body atlas data. In the benchmark datasets the weighted median normalization either removes or strongly reduces the batch effects between different TMT plexes and results in clustering by biology. In datasets including a reference channel, we find that weighted median normalization performs as well or better when the reference channel is ignored and only the sample channel intensities are used, suggesting that the measurement of a reference channel is unnecessary when using weighted median normalization in MaxQuant. We demonstrate that MaxQuant including the weighted median normalization performs well on multi-notch MS3 data, as well as on phosphorylation data. Data Summary: Each folder contains MaxQuant output tables used for data analysis with their respectively mqpar files. Please use the MaxQuant version specified in each dataset to open mqpar files. Perseus sessions are provided when Perseus was used for downstream analyses. Please use Perseus version Perseus version 2.1.2 to load the sessions.

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Institutions

Max-Planck-Institut fur Biochemie

Categories

Biochemistry, Bioinformatics, Mass Spectrometry, Proteomics, Data Analysis, Omics

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