MassIVE MSV000096130

Imported Reanalysis Dataset Public PXD012308

Deep motif deconvolution of HLA-II peptidomes

Description

CD4 T cells are key for priming and regulating immune recognition of infected and cancer cells, but predictions of class II epitopes have limited accuracy. We profiled over 100’000 HLA-II ligands by Mass Spectrometry and developed a novel motif deconvolution algorithm to analyze these data. Our work demonstrates substantial improvements in the definition of HLA-II binding motifs and enhanced accuracy in HLA-II ligand and class II epitope predictions. [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Immunopeptidomics ; Ligand predictions ; Mass spectrometry ; Hla class ii ; Neoantigens ; DatasetType:Proteomics

Contact

Principal Investigators:
(in alphabetical order)
Michal Bassani-Sternberg, Dr Michal BASSANI-STERNBERG � Group leader Laboratory Hi-TIDe: Immunopeptidomics Head of clinical Mass spectrometry unit Center of experimental therapeutics Department of oncology UNIL CHUV Ludwig Institute for Cancer Research Lausanne Biop�le 3 Chemin des Boveresses 155, CH-1066 Lausanne, N/A
Submitting User: ccms

Publications

Racle J, Michaux J, Rockinger GA, Arnaud M, Bobisse S, Chong C, Guillaume P, Coukos G, Harari A, Jandus C, Bassani-Sternberg M, Gfeller D.
Robust prediction of HLA class II epitopes by deep motif deconvolution of immunopeptidomes.
Nat Biotechnol. 2019 Nov;37(11):1283-1286. Epub 2019 Oct 14.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.