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Title:

Re-analysis of ProteomicsDB using an accurate, sensitive and scalable false discovery rate estimation approach for protein groups

Document type:
Zeitschriftenaufsatz
Author(s):
The, Matthew; Samaras, Patroklos; Kuster, Bernhard; Wilhelm, Mathias
Abstract:
Estimating false discovery rates (FDRs) of protein identification continues to be an important topic in mass spectrometry-based proteomics, particularly when analyzing very large data sets. One performant method for this purpose is the Picked Protein FDR approach which is based on a target-decoy competition strategy on the protein level that ensures that FDRs scale to large data sets. Here, we present an extension to this method that can also deal with protein groups, i.e. proteins that share co...     »
Keywords:
BayBioMS; Large-scale proteomics; ProteomicsDB; picked protein FDR; protein false discovery rate estimation; protein inference.
Journal title:
Molecular & Cellular Proteomics
Year:
2022
Pages contribution:
100437
Fulltext / DOI:
doi:10.1016/j.mcpro.2022.100437
Publisher:
Elsevier BV
E-ISSN:
1535-9476
Date of publication:
01.11.2022
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