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PXD022280 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleSpectral prediction features as a solution for the search space size problem in proteogenomics
DescriptionProteogenomics approaches often struggle with the distinction between right and false peptide-to-spectrum matches as the database size enlarges. However, features extracted from tandem mass spectrometry intensity predictors can enhance the peptide identification rate and can provide extra confidence for spectral matching in a proteogenomic context. To that end, features from the spectral intensity pattern predictors MS2PIP and Prosit were combined with the canonical scores from MaxQuant in the Percolator post-processing tool for protein databases constructed from RNA-seq and ribosome profiling analyses. The presented results provide evidence that this approach enhances the peptide identification power in a proteogenomic setting and in the meantime they lead to the validation of new proteoforms with elevated stringency. In this online repository, we submitted the conventional proteomic search results with MaxQuant against the custom nanopore RNA-seq-based search space. All other results can be found in the supplemental materials of the manuscript, in SRA (sequencing data) or under ProteomeXChange Project PXD011353 (as this is original data from a previuos paper).
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterSteven Verbruggen
SpeciesList scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationListmonohydroxylated residue; acetylated residue
InstrumentQ Exactive HF
Dataset History
RevisionDatetimeStatusChangeLog Entry
02020-11-02 00:01:47ID requested
12021-03-26 05:26:07announced
22021-04-07 05:29:20announced2021-04-07: Updated publication reference for PubMed record(s): 31040227, 33823297.
32021-04-07 21:57:13announced2021-04-08: Updated project metadata.
42021-04-07 21:59:38announced2021-04-08: Updated project metadata.
Publication List
Verbruggen S, Gessulat S, Gabriels R, Matsaroki A, Van de Voorde H, Kuster B, Degroeve S, Martens L, Van Criekinge W, Wilhelm M, Menschaert G, Spectral prediction features as a solution for the search space size problem in proteogenomics. Mol Cell Proteomics, ():100076(2021) [pubmed]
Keyword List
submitter keyword: proteogenomics
spectrum predictor
nanopore sequencing
ribosome profiling
intensity features
machine learning
Contact List
Gerben Menschaert
contact affiliationBioBix, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, Ghent, Belgium
contact emailGerben.Menschaert@UGent.be
lab head
Steven Verbruggen
contact affiliationBioBix
contact emailSteven.Verbruggen@UGent.be
dataset submitter
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