Cited by 0Genomics and Rare DiseasesEnzyme Structure and FunctionProtein Structure and Dynamics

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3Dmapper: a command line tool for BioBank-scale mapping of variants to protein structures

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Ruiz-Serra, Victoria, Valentini, Samuel, Madroñero, Sergi, Valencia, Alfonso, Porta-Pardo, Eduard·2024·Bioinformatics

Published version of a preprint

Abstract

Motivation: The interpretation of genomic data is crucial to understand the molecular mechanisms of biological processes. Protein structures play a vital role in facilitating this interpretation by providing functional context to genetic coding variants. However, mapping genes to proteins is a tedious and error-prone task due to inconsistencies in data formats. Over the past two decades, numerous tools and databases have been developed to automatically map annotated positions and variants to protein structures. However, most of these tools are web-based and not well-suited for large-scale genomic data analysis. Results: To address this issue, we introduce 3Dmapper, a stand-alone command-line tool developed in Python and R. It systematically maps annotated protein positions and variants to protein structures, providing a solution that is both efficient and reliable. Availability and implementation: https://github.com/vicruiser/3Dmapper

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Research works printed but not linked: 20

  1. Bailey, 2018, Comprehensive characterization of cancer driver genes and mutations, Cell, 173, 371, 10.1016/j.cell.2018.02.060 · DOI · Paper page
  2. Baldock, 2019, RAD51D splice variants and cancer-associated mutations reveal XRCC2 interaction to be critical for homologous recombination, DNA Repair (Amst), 76, 99, 10.1016/j.dnarep.2019.02.008 · DOI
  3. Bamshad, 2011, Exome sequencing as a tool for Mendelian disease gene discovery, Nat Rev Genet, 12, 745, 10.1038/nrg3031 · DOI
  4. Berman, 2000, The protein data bank, Nucleic Acids Res, 28, 235, 10.1093/nar/28.1.235 · DOI · Paper page
  5. Cheng, 2021, Comprehensive characterization of protein–protein interactions perturbed by disease mutations, Nat Genet, 53, 342, 10.1038/s41588-020-00774-y · DOI
  6. Drew, 2021, hu.MAP 2.0: integration of over 15,000 proteomic experiments builds a global compendium of human multiprotein assemblies, Mol Syst Biol, 17, e10016, 10.15252/msb.202010016 · DOI
  7. Goddard, 2018, UCSF ChimeraX: meeting modern challenges in visualization and analysis, Protein Sci, 27, 14, 10.1002/pro.3235 · DOI · Paper page
  8. Grant, 2021, The Bio3D packages for structural bioinformatics, Protein Sci, 30, 20, 10.1002/pro.3923 · DOI
  9. Hubbard, 2002, The ensembl genome database project, Nucleic Acids Res, 30, 38, 10.1093/nar/30.1.38 · DOI
  10. Karczewski, 2020, The mutational constraint spectrum quantified from variation in 141,456 humans, Nature, 581, 434, 10.1038/s41586-020-2308-7 · DOI · Paper page
  11. Landrum, 2018, ClinVar: improving access to variant interpretations and supporting evidence, Nucleic Acids Res, 46, D1062, 10.1093/nar/gkx1153 · DOI · Paper page
  12. Li, 2023, Pan-cancer proteogenomics connects oncogenic drivers to functional states, Cell, 186, 3921, 10.1016/j.cell.2023.07.014 · DOI
  13. Luck, 2020, A reference map of the human binary protein interactome, Nature, 580, 402, 10.1038/s41586-020-2188-x · DOI · Paper page
  14. Mosca, 2013, Interactome3D: adding structural details to protein networks, Nat Methods, 10, 47, 10.1038/nmeth.2289 · DOI · Paper page
  15. Peterson, 2010, DMDM: domain mapping of disease mutations, Bioinformatics, 26, 2458, 10.1093/bioinformatics/btq447 · DOI
  16. Porta-Pardo, 2016, Mutation drivers of immunological responses to cancer, Cancer Immunol Res, 4, 789, 10.1158/2326-6066.CIR-15-0233 · DOI
  17. The UniProt Consortium, 2023, UniProt: the universal protein knowledgebase in 2023, Nucleic Acids Res, 51, D523, 10.1093/nar/gkac1052 · DOI · Paper page
  18. Wickham, 2009, ggplot2: Elegant graphics for data analysis., 1, 10.1007/978-0-387-98141-3 · DOI · Paper page
  19. Wu, 2011, Rare-variant association testing for sequencing data with the sequence kernel association test, Am J Hum Genet, 89, 82, 10.1016/j.ajhg.2011.05.029 · DOI
  20. Yang, 2015, Protein domain-level landscape of cancer-type-specific somatic mutations, PLoS Comput Biol, 11, e1004147, 10.1371/journal.pcbi.1004147 · DOI

Metadata

Authors
Ruiz-Serra, V., Valentini, S., Madroñero, S., Valencia, A., & Porta-Pardo, E.
Affiliations
  • Barcelona Supercomputing Center (BSC)
  • University of Trento (IT)
  • Josep Carreras Leukaemia Research Institute (ES)
  • Institució Catalana de Recerca i Estudis Avançats (ES)
Venue
Bioinformatics
Published
2024-03-29
Volume
40
Issue
4
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
OpenAlex
W4393407391
Cited by
0
References
4
FWCI
0.00
Type
journal article
Language
en
Open access
Locations
  • Bioinformatics (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • UPCommons institutional repository (Universitat Politècnica de Catalunya) (submittedVersion, cc-by-nc-nd)
  • Dipòsit Digital de Documents de la UAB (Universitat Autònoma de Barcelona) (submittedVersion, cc-by)
Funders
  • La Caixa Junior Leader Fellowship (LCF/BQ/PI18/11630003)
  • Spanish Ministry of Science (RYC2019-026415-I, PID2019-107043RA-I00)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
Keywords
protein structure, genetic variants, genomic data interpretation, command-line tool, genome annotation
MeSH terms
Proteins, Software, Biological Specimen Banks, Genomics

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