DIAgui: a Shiny application to process the output from DIA-NN
Author:
Affiliation:
1. Aix-Marseille University, INSERM, CNRS, Institut Paoli-Calmettes, CRCM, Marseille Protéomique , Marseille F-13009, France
2. Centrale Marseille School , Marseille F-13013, France
Abstract
Funder
National Institute of Health
Medical Research of France
Marseille Protéomique
Publisher
Oxford University Press (OUP)
Link
https://academic.oup.com/bioinformaticsadvances/advance-article-pdf/doi/10.1093/bioadv/vbae001/55676925/vbae001.pdf
Reference10 articles.
1. Absolute quantification strategies in proteomics based on mass spectrometry;Brönstrup;Expert Rev Proteomics,2004
2. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ;Cox;Mol Cell Proteomics,2014
3. DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput;Demichev;Nat Methods,2020
4. Extensive and accurate benchmarking of DIA acquisition methods and software tools using a complex proteomic standard;Gotti;J Proteome Res,2021
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