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MaveDB v2: a curated community database with over three million variant effects from multiplexed functional assays

View ORCID ProfileAlan F Rubin, Joseph K Min, Nathan J Rollins, Estelle Y Da, Daniel Esposito, Matthew Harrington, Jeremy Stone, Aisha Haley Bianchi, Mafalda Dias, Jonathan Frazer, Yunfan Fu, Molly Gallaher, Iris Li, Olivia Moscatelli, Jesslyn YL Ong, Joshua E Rollins, Matthew J Wakefield, Shenyi “Sunny” Ye, Amy Tam, Abbye E McEwen, Lea M Starita, Vanessa L Bryant, Debora S Marks, Douglas M Fowler
doi: https://doi.org/10.1101/2021.11.29.470445
Alan F Rubin
1Bioinformatics Division, WEHI, Parkville, Australia
2Department of Medical Biology, University of Melbourne, Parkville, Australia
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  • ORCID record for Alan F Rubin
  • For correspondence: alan.rubin@wehi.edu.au debbie@hms.harvard.edu dfowler@uw.edu
Joseph K Min
3Department of Systems Biology, Harvard Medical School, Boston, USA
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Nathan J Rollins
3Department of Systems Biology, Harvard Medical School, Boston, USA
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Estelle Y Da
1Bioinformatics Division, WEHI, Parkville, Australia
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Daniel Esposito
1Bioinformatics Division, WEHI, Parkville, Australia
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Matthew Harrington
4Department of Genome Sciences, University of Washington, Seattle, USA
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Jeremy Stone
5Brotman Baty Institute for Precision Medicine, Seattle, USA
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Aisha Haley Bianchi
4Department of Genome Sciences, University of Washington, Seattle, USA
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Mafalda Dias
3Department of Systems Biology, Harvard Medical School, Boston, USA
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Jonathan Frazer
3Department of Systems Biology, Harvard Medical School, Boston, USA
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Yunfan Fu
1Bioinformatics Division, WEHI, Parkville, Australia
2Department of Medical Biology, University of Melbourne, Parkville, Australia
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Molly Gallaher
4Department of Genome Sciences, University of Washington, Seattle, USA
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Iris Li
1Bioinformatics Division, WEHI, Parkville, Australia
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Olivia Moscatelli
2Department of Medical Biology, University of Melbourne, Parkville, Australia
6Immunology Division, WEHI, Parkville, Australia
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Jesslyn YL Ong
6Immunology Division, WEHI, Parkville, Australia
7Department of Microbiology and Immunology, University of Melbourne, Parkville, Australia
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Joshua E Rollins
3Department of Systems Biology, Harvard Medical School, Boston, USA
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Matthew J Wakefield
1Bioinformatics Division, WEHI, Parkville, Australia
2Department of Medical Biology, University of Melbourne, Parkville, Australia
8Department of Obstetrics and Gynaecology, University of Melbourne, Parkville, Australia
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Shenyi “Sunny” Ye
4Department of Genome Sciences, University of Washington, Seattle, USA
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Amy Tam
3Department of Systems Biology, Harvard Medical School, Boston, USA
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Abbye E McEwen
4Department of Genome Sciences, University of Washington, Seattle, USA
5Brotman Baty Institute for Precision Medicine, Seattle, USA
9Department of Laboratory Medicine and Pathology, University of Washington, Seattle, USA
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Lea M Starita
4Department of Genome Sciences, University of Washington, Seattle, USA
5Brotman Baty Institute for Precision Medicine, Seattle, USA
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Vanessa L Bryant
2Department of Medical Biology, University of Melbourne, Parkville, Australia
6Immunology Division, WEHI, Parkville, Australia
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Debora S Marks
3Department of Systems Biology, Harvard Medical School, Boston, USA
10Broad Institute of Harvard and MIT
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  • For correspondence: alan.rubin@wehi.edu.au debbie@hms.harvard.edu dfowler@uw.edu
Douglas M Fowler
4Department of Genome Sciences, University of Washington, Seattle, USA
11Department of Bioengineering, University of Washington, Seattle, United States
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  • For correspondence: alan.rubin@wehi.edu.au debbie@hms.harvard.edu dfowler@uw.edu
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Abstract

A central problem in genomics is understanding the effect of individual DNA variants. Multiplexed Assays of Variant Effect (MAVEs) can help address this challenge by measuring all possible single nucleotide variant effects in a gene or regulatory sequence simultaneously. Here we describe MaveDB v2, which has become the database of record for MAVEs. MaveDB now contains a large fraction of published studies, comprising over two hundred datasets and three million variant effect measurements. We created tools and APIs to streamline data submission and access, transforming MaveDB into a hub for the analysis and dissemination of these impactful datasets.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted January 18, 2022.
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MaveDB v2: a curated community database with over three million variant effects from multiplexed functional assays
Alan F Rubin, Joseph K Min, Nathan J Rollins, Estelle Y Da, Daniel Esposito, Matthew Harrington, Jeremy Stone, Aisha Haley Bianchi, Mafalda Dias, Jonathan Frazer, Yunfan Fu, Molly Gallaher, Iris Li, Olivia Moscatelli, Jesslyn YL Ong, Joshua E Rollins, Matthew J Wakefield, Shenyi “Sunny” Ye, Amy Tam, Abbye E McEwen, Lea M Starita, Vanessa L Bryant, Debora S Marks, Douglas M Fowler
bioRxiv 2021.11.29.470445; doi: https://doi.org/10.1101/2021.11.29.470445
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MaveDB v2: a curated community database with over three million variant effects from multiplexed functional assays
Alan F Rubin, Joseph K Min, Nathan J Rollins, Estelle Y Da, Daniel Esposito, Matthew Harrington, Jeremy Stone, Aisha Haley Bianchi, Mafalda Dias, Jonathan Frazer, Yunfan Fu, Molly Gallaher, Iris Li, Olivia Moscatelli, Jesslyn YL Ong, Joshua E Rollins, Matthew J Wakefield, Shenyi “Sunny” Ye, Amy Tam, Abbye E McEwen, Lea M Starita, Vanessa L Bryant, Debora S Marks, Douglas M Fowler
bioRxiv 2021.11.29.470445; doi: https://doi.org/10.1101/2021.11.29.470445

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