An MSstats workflow for detecting differentially abundant proteins in large-scale data-independent acquisition mass spectrometry experiments with FragPipe processing

Devon Kohler, Mateusz Staniak, Fengchao Yu, Alexey I. Nesvizhskii, Olga Vitek

Published: 2024-05-19 DOI: 10.1038/s41596-024-01000-3

statistical analysis

proteomics

DIA experiments

MSstats

FragPipe

AI 解读

Genetic manipulation and immortalized culture of ex vivo primary human germinal center B cells

The cell-line-derived subcutaneous tumor model in preclinical cancer research

Subcellular patch-clamp techniques for single-bouton stimulation and simultaneous pre- and postsynaptic recording at cortical synapses

NovoSpaRc: flexible spatial reconstruction of single-cell gene expression with optimal transport

Genome-wide pooled CRISPR screening in neurospheres

High-throughput cultivation and identification of bacteria from the plant root microbiota

Viral crosslinking and solid-phase purification enables discovery of ribonucleoprotein complexes on incoming RNA virus genomes

Mitochondrial single-cell ATAC-seq for high-throughput multi-omic detection of mitochondrial genotypes and chromatin accessibility

Addendum: Micro-CT acquisition and image processing to track and characterize pulmonary nodules in mice

Multiplexed single-cell proteomics using SCoPE2

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Sections

Figures

References

Introduction
Materials
- Equipment
- Equipment setup
Procedure 1: MSstatsShiny analysis pipeline
Procedure 2: MSstats code analysis pipeline
Troubleshooting
Timing
- Procedure 1
- Procedure 2
Anticipated results
Acknowledgements

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An MSstats workflow for detecting differentially abundant proteins in large-scale data-independent acquisition mass spectrometry experiments with FragPipe processing

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