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

Alan F. Rubin; Joseph 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 G. Moscatelli; Jesslyn 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:10.1101/2021.11.29.470445

GenomicsbioRxivNov 29, 2021

Preprint

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

Alan F. Rubin iD, Joseph Min iD, Nathan J. Rollins iD, Estelle Y. Da iD, Daniel Esposito iD, Matthew Harrington, Jeremy Stone iD, Aisha Haley Bianchi iD, Mafalda Dias iD, Jonathan Frazer iD, Yunfan Fu iD, Molly Gallaher, Iris Li, Olivia G. Moscatelli iD, Jesslyn Ong, Joshua E. Rollins iD, Matthew J. Wakefield iD, Shenyi “Sunny” Ye, Amy Tam iD, Abbye E. McEwen iD, Lea M. Starita iD, Vanessa L. Bryant iD, Debora S. Marks iD, Douglas M. Fowler iD

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.

PDF DOI