precisionFDA Truth Challenge V2: Calling variants from short- and long-reads in difficult-to-map regions Article Swipe
YOU?
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· 2020
· Open Access
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· DOI: https://doi.org/10.1101/2020.11.13.380741
Summary The precisionFDA Truth Challenge V2 aimed to assess the state-of-the-art of variant calling in difficult-to-map regions and the Major Histocompatibility Complex (MHC). Starting with FASTQ files, 20 challenge participants applied their variant calling pipelines and submitted 64 variant callsets for one or more sequencing technologies (~35X Illumina, ~35X PacBio HiFi, and ~50X Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with the new GIAB benchmark sets and genome stratifications. Challenge submissions included a number of innovative methods for all three technologies, with graph-based and machine-learning methods scoring best for short-read and long-read datasets, respectively. New methods out-performed the 2016 Truth Challenge winners, and new machine-learning approaches combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2020.11.13.380741
- https://www.biorxiv.org/content/biorxiv/early/2021/02/03/2020.11.13.380741.full.pdf
- OA Status
- green
- Cited By
- 66
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3101227640
Raw OpenAlex JSON
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https://openalex.org/W3101227640Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2020.11.13.380741Digital Object Identifier
- Title
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precisionFDA Truth Challenge V2: Calling variants from short- and long-reads in difficult-to-map regionsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-11-15Full publication date if available
- Authors
-
Nathan D. Olson, Justin Wagner, Jennifer McDaniel, Sarah H. Stephens, Samuel T. Westreich, Anish G. Prasanna, Elaine Johanson, Emily S. Boja, Ezekiel J. Maier, Omar Serang, David Jáspez, José M. Lorenzo-Salazar, Adrián Muñoz‐Barrera, Luis A. Rubio‐Rodríguez, Carlos Flores, Konstantinos Kyriakidis, Andigoni Malousi, Kishwar Shafin, Trevor Pesout, Miten Jain, Benedict Paten, Pi-Chuan Chang, Alexey Kolesnikov, Maria Nattestad, Gunjan Baid, Sidharth Goel, Howard H. Yang, Andrew Carroll, Robert Eveleigh, Mathieu Bourgey, Guillaume Bourque, Gen Li, MA ChouXian, LinQi Tang, DU YuanPing, Shaowei Zhang, Jordi Morata, Raúl Tonda, Genı́s Parra, Jean-Rémi Trotta, Christian Brueffer, Sinem Demirkaya-Budak, Duygu Kabakci-Zorlu, Deniz Turgut, Özem Kalay, Güngör Budak, Kübra Narcı, Elif Acar Arslan, Matthew A. Brown, Ivan J. Johnson, Alexey Dolgoborodov, Vladimir Semenyuk, Amit Jain, H. Serhat Tetikol, Varun Jain, Mike Ruehle, Bryan R. Lajoie, Cooper Roddey, Severine Catreux, Rami Mehio, Mian Umair Ahsan, Qian Liu, Kai Wang, Sayed Mohammad Ebrahim Sahraeian, Li Tai Fang, Marghoob Mohiyuddin, Calvin Hung, Chirag Jain, Hanying Feng, Zhipan Li, Luoqi Chen, Fritz J. Sedlazeck, Justin M. ZookList of authors in order
- Landing page
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https://doi.org/10.1101/2020.11.13.380741Publisher landing page
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https://www.biorxiv.org/content/biorxiv/early/2021/02/03/2020.11.13.380741.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2021/02/03/2020.11.13.380741.full.pdfDirect OA link when available
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Benchmarking, Computer science, Nanopore sequencing, Benchmark (surveying), Identification (biology), Data science, Crowdsourcing, Data mining, Computational biology, Artificial intelligence, Genome, Machine learning, Biology, Genetics, Geography, World Wide Web, Cartography, Gene, Botany, Marketing, BusinessTop concepts (fields/topics) attached by OpenAlex
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66Total citation count in OpenAlex
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2025: 4, 2024: 6, 2023: 8, 2022: 21, 2021: 23Per-year citation counts (last 5 years)
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30Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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