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MassIVE-KB Knowledge Base spectral library of Human HCD spectra

ABSTRACT: The individual contributions of many laboratories and experiments have advanced the proteomics community but the lack of an error-controlled community wide knowledge base that fully tracks provenance limits the ability for researchers to benefit from this progress. MassIVE-KB is a spectral library resource that aggregates identified spectra from over 30TB of human HCD proteomics data into a reusable resource that can be used to estimate the progress of the proteomics community. MassIVE-KB contains over 2.1 million precursors from 19,610 proteins and increased coverage to over 6 million amino acids (54% of the proteome) with strict false discovery controls at the spectrum, precursor, and protein level. Further, MassIVE-KB reveals previously missing proteomics evidence for 723 proteins, complete with fully traceable provenance back to the data, search parameters, and library creation procedures. This MassIVE-KB resource capitalizes on the whole communityâ€™s data to better inform experimental design, identify new data using library search tools, and provide the tools for the community to build their own specialized knowledge bases.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Nuno Bandeira

PROVIDER: MSV000081142 | MassIVE | Tue Jun 06 11:52:00 BST 2017

REPOSITORIES: MassIVE

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Project description:To create a dataset of PSMs that does not exhibit tryptic bias, we selected PSMs with a uniform distribution of amino acids at the C-terminal peptide positions from two datasets: MassIVE-KB [Wang2018] and PROSPECT [Shouman2022]. The MassIVE-KB dataset contains 30 million PSMs and consists entirely of data generated using trypsin; hence, only a small proportion of the MassIVE-KB peptides do not end in K or R, corresponding to those that appear at the C-terminus of the corresponding protein. The PROSPECT dataset is a collection of 61 million PSMs generated from synthetic peptides. To avoid overrepresentation of some peptides in this dataset, we randomly selected at most 100 PSMs per unique peptide, similar to the processing that was done during the creation of the MassIVE-KB dataset. This pre-selection step reduced the size of the PROSPECT dataset to 12.6 million PSMs. Finally, to create a non-enzymatic dataset containing 1 million peptides, we selected 50,000 PSMs for each canonical amino acid. These PSMs were selected at random from MassIVE-KB, then supplemented as necessary from PROSPECT to obtain the desired count (see Yilmaz et al. [Yilmaz2023] Supplementary Table S1). This dataset contained PSMs from 247,859 unique peptides, which were randomly split into training, validation and test sets in the ratio 80/10/10. FTP directory contains the mgf files corresponding to train, validation and test splits. [Wang2018] M. Wang, J. Wang, J. Carver, B. Pullman, S. Won Cha, N. Bandeira, "Assembling the Community-Scale Discoverable Human Proteome", Cell Systems, Volume 7, Issue 4, 2018. [Shouman2022] O. Shouman, W. Gabriel, V. Giurcoiu, V. Sternlicht, M. Wilhelm, "PROSPECT: Labeled Tandem Mass Spectrometry Dataset for Machine Learning in Proteomics", NeurIPS Datasets and Benchmarks, 2022 [Yilmaz2023] M. Yilmaz*, W. Fondrie*, W. Bittremieux, R. Nelson, V. Ananth, S. Oh, and W. Noble,"Sequence-to-sequence translation from mass spectra to peptides with a transformer model", bioRxiv, 2023

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MassIVE-KB Knowledge Base spectral library of Human HCD spectra

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