Evidence map›Paper›PMID 38292474›Full record

ArticleComputational and structural biotechnology journal2024

PgxSAVy: A tool for comprehensive evaluation of variant peptide quality in proteogenomics - catching the (un)usual suspects.

Anurag Raj, Suruchi Aggarwal, Prateek Singh, Amit Kumar Yadav, Debasis Dash

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Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Anurag RajG. N. Ramachandran Knowledge Centre for Genomics Informatics, CSIR - Institute of Genomics and Integrative Biology, New Delhi, India.
Suruchi AggarwalComputational and Mathematical Biology Centre (CMBC), 3rd Milestone, Faridabad-Gurgaon Expressway, Faridabad, Haryana 121001, India.
Prateek SinghG. N. Ramachandran Knowledge Centre for Genomics Informatics, CSIR - Institute of Genomics and Integrative Biology, New Delhi, India.
Amit Kumar YadavComputational and Mathematical Biology Centre (CMBC), 3rd Milestone, Faridabad-Gurgaon Expressway, Faridabad, Haryana 121001, India.
Debasis DashG. N. Ramachandran Knowledge Centre for Genomics Informatics, CSIR - Institute of Genomics and Integrative Biology, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Variant peptides resulting from single nucleotide polymorphisms (SNPs) can lead to aberrant protein functions and have translational potential for disease diagnosis and personalized therapy. Variant peptides detected by proteogenomics are fraught with high number of false positives, but there is no uniform and comprehensive approach to assess variant quality across analysis pipelines. Despite class-specific FDR along with ad-hoc filters, the problem is far from solved. These protocols are typically manual and tedious, and thus not uniform across labs. We demonstrate that variant peptide rescoring, integrated with intensity, variant event information and search result features, allows better discrimination of correct variant peptides. Implemented into PgxSAVy - a tool for quality control of variant peptides, this method can tackle the high rate of false positives. PgxSAVy provides a rigorous framework for quality control and annotations of variant peptides on the basis of (i) variant quality, (ii) isobaric masses, and (iii) disease annotation. PgxSAVy demonstrated high accuracy by identifying true variants with 98.43% accuracy on simulated data. Large-scale proteogenomic reanalysis of ∼2.8 million spectra (PXD004010 and PXD001468) resulted in 12,705 variant peptide spectrum matches (PSMs), of which PgxSAVy evaluated 3028 (23.8%), 1409 (11.1%) and 8268 (65.1%) as confident, semi-confident and doubtful respectively. PgxSAVy also annotates the variants based on their pathogenicity and provides support for assisted manual validation. The analysis of proteins carrying variants can provide fine granularity in discovering important pathways. PgxSAVy will advance personalized medicine by providing a comprehensive framework for quality control and prioritization of proteogenomics variants. PgxSAVy is freely available at https://pgxsavy.igib.res.in/ as a webserver and https://github.com/anuragraj/PgxSAVy as a stand-alone tool.

Indexed as

False discovery rateMass spectrometryMutationsPgxSAVyProteoformsProteogenomicsProteomicsQuality assessmentSAPsSAVsSNPsVariant peptides

Identifiers

PMID38292474
PMCPMC10825656

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.