Benjamin Pullman

University of Montana

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Nuno Bandeira

University of California, San Diego

Jeremy Carver

University of Montana

Yasset Pérez‐Riverol

Wellcome Trust

Eric W. Deutsch

Institute for Systems Biology

Juan Antonio Vizcaíno

European Bioinformatics Institute

Shin Kawano

Research Organization of Information and Systems

Mingxun Wang

University of California, Riverside

Ralf Gabriels

VIB-UGent Center for Medical Biotechnology

Joshua Klein

Boston University

Wout Bittremieux

University of Antwerp

Cooperative Institutions

AstraZeneca (United Kingdom)

University of California, San Diego

University of Montana

AstraZeneca (Brazil)

AstraZeneca (Sweden)

University of Cambridge

AstraZeneca (United States)

Wellcome Trust

Genomics (United Kingdom)

European Bioinformatics Institute

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Index-Based, High-Dimensional, Cosine Threshold Querying with Optimality Guarantees

Yuliang Li Jianguo Wang Benjamin Pullman Nuno Bandeira Yannis Papakonstantinou

Given a database of vectors, a cosine threshold query returns all vectors in the database having cosine similarity to a query vector above a given threshold. These queries arise naturally in many applications, such as document retrieval, image search, and mass spectrometry. The present paper considers the efficient evaluation of such queries, providing novel optimality guarantees and exhibiting good performance on real datasets. We take as a starting point Fagin's well-known Threshold Algorithm (TA), which can be used to answer cosine threshold queries as follows: an inverted index is first built from the database vectors during pre-processing; at query time, the algorithm traverses the index partially to gather a set of candidate vectors to be later verified against the similarity threshold. However, directly applying TA in its raw form misses significant optimization opportunities. Indeed, we first show that one can take advantage of the fact that the vectors can be assumed to be normalized, to obtain an improved, tight stopping condition for index traversal and to efficiently compute it incrementally. Then we show that one can take advantage of data skewness to obtain better traversal strategies. In particular, we show a novel traversal strategy that exploits a common data skewness condition which holds in multiple domains including mass spectrometry, documents, and image databases. We show that under the skewness assumption, the new traversal strategy has a strong, near-optimal performance guarantee. The techniques developed in the paper are quite general since they can be applied to a large class of similarity functions beyond cosine.

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10.4230/lipics.icdt.2019.11

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MassIVE.quant: a community resource of quantitative mass spectrometry–based proteomics datasets

Nature Methods (2020)

Meena Choi Jeremy Carver Cristina Chiva Manuel Tzouros Ting Huang

10.1038/s41592-020-0955-0

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GNPS Dashboard: Collaborative Analysis of Mass Spectrometry Data in the Web Browser

bioRxiv (Cold Spring Harbor Laboratory) (2021)

Daniel Petras Vanessa V. Phelan Deepa Acharya Andrew E. Allen Allegra T. Aron

Abstract Access to web-based platforms has enabled scientists to perform research remotely. A critical aspect of mass spectrometry data analysis is the inspection, analysis, and visualization of the raw data to validate data quality and confirm statistical observations. We developed the GNPS Dashboard, a web-based data visualization tool, to facilitate synchronous collaborative inspection, visualization, and analysis of private and public mass spectrometry data remotely.

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10.1101/2021.04.05.438475

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Universal Spectrum Identifier for mass spectra

Nature Methods (2021)

Eric W. Deutsch Yasset Pérez‐Riverol Jeremy Carver Shin Kawano Luis Mendoza

10.1038/s41592-021-01184-6

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microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data

Nature Microbiology (2024)

Simone Zuffa Robin Schmid Anelize Bauermeister Paulo Wender Portal Gomes Andrés Mauricio Caraballo‐Rodríguez

Abstract microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms’ role in ecology and human health.

Fragmentation

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10.1038/s41564-023-01575-9

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Genetic architecture of telomere length in 462,666 UK Biobank whole-genome sequences

Nature Genetics (2024)

Oliver S. Burren Ryan S. Dhindsa Sri V. V. Deevi Sean Wen Abhishek Nag

Telomeres protect chromosome ends from damage and their length is linked with human disease and aging. We developed a joint telomere length metric, combining quantitative PCR and whole-genome sequencing measurements from 462,666 UK Biobank participants. This metric increased SNP heritability, suggesting that it better captures genetic regulation of telomere length. Exome-wide rare-variant and gene-level collapsing association studies identified 64 variants and 30 genes significantly associated with telomere length, including allelic series in ACD and RTEL1. Notably, 16% of these genes are known drivers of clonal hematopoiesis-an age-related somatic mosaicism associated with myeloid cancers and several nonmalignant diseases. Somatic variant analyses revealed gene-specific associations with telomere length, including lengthened telomeres in individuals with large SRSF2-mutant clones, compared with shortened telomeres in individuals with clonal expansions driven by other genes. Collectively, our findings demonstrate the impact of rare variants on telomere length, with larger effects observed among genes also associated with clonal hematopoiesis.

Genetic architecture

10.1038/s41588-024-01884-7

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Citations (7)