Reference : Diagnostics and correction of batch effects in large-scale proteomic studies: a tutorial.
Scientific journals : Article
Life sciences : Biochemistry, biophysics & molecular biology
http://hdl.handle.net/10993/48044
Diagnostics and correction of batch effects in large-scale proteomic studies: a tutorial.
English
Čuklina, Jelena [> >]
Lee, Chloe H. [> >]
Williams, Evan mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Gene Expression and Metabolism]
Sajic, Tatjana [> >]
Collins, Ben C. [> >]
Rodríguez Martínez, María [> >]
Sharma, Varun S. [> >]
Wendt, Fabian [> >]
Goetze, Sandra [> >]
Keele, Gregory R. [> >]
Wollscheid, Bernd [> >]
Aebersold, Ruedi [> >]
Pedrioli, Patrick G. A. [> >]
2021
Molecular systems biology
17
8
e10240
Yes
1744-4292
1744-4292
England
[en] batch effects ; data analysis ; large-scale proteomics ; normalization ; quantitative proteomics
[en] Advancements in mass spectrometry-based proteomics have enabled experiments encompassing hundreds of samples. While these large sample sets deliver much-needed statistical power, handling them introduces technical variability known as batch effects. Here, we present a step-by-step protocol for the assessment, normalization, and batch correction of proteomic data. We review established methodologies from related fields and describe solutions specific to proteomic challenges, such as ion intensity drift and missing values in quantitative feature matrices. Finally, we compile a set of techniques that enable control of batch effect adjustment quality. We provide an R package, "proBatch", containing functions required for each step of the protocol. We demonstrate the utility of this methodology on five proteomic datasets each encompassing hundreds of samples and consisting of multiple experimental designs. In conclusion, we provide guidelines and tools to make the extraction of true biological signal from large proteomic studies more robust and transparent, ultimately facilitating reliable and reproducible research in clinical proteomics and systems biology.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/48044
10.15252/msb.202110240
© 2021 The Authors. Published under the terms of the CC BY 4.0 license.

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