A web application and service for imputing and visualizing missense variant effect maps

SUMMARY: The promise of personalized genomic medicine depends on our ability to assess the functional impact of rare sequence variation. Multiplexed assays can experimentally measure the functional impact of missense variants on a massive scale. However, even after such assays, many missense variant...

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Autores principales: Wu, Yingzhou, Weile, Jochen, Cote, Atina G, Sun, Song, Knapp, Jennifer, Verby, Marta, Roth, Frederick P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6735881/
https://www.ncbi.nlm.nih.gov/pubmed/30649215
http://dx.doi.org/10.1093/bioinformatics/btz012
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author Wu, Yingzhou
Weile, Jochen
Cote, Atina G
Sun, Song
Knapp, Jennifer
Verby, Marta
Roth, Frederick P
author_facet Wu, Yingzhou
Weile, Jochen
Cote, Atina G
Sun, Song
Knapp, Jennifer
Verby, Marta
Roth, Frederick P
author_sort Wu, Yingzhou
collection PubMed
description SUMMARY: The promise of personalized genomic medicine depends on our ability to assess the functional impact of rare sequence variation. Multiplexed assays can experimentally measure the functional impact of missense variants on a massive scale. However, even after such assays, many missense variants remain poorly measured. Here we describe a software pipeline and application to impute missing information in experimentally determined variant effect maps. AVAILABILITY AND IMPLEMENTATION: http://impute.varianteffect.org source code: https://github.com/joewuca/imputation. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-67358812019-09-16 A web application and service for imputing and visualizing missense variant effect maps Wu, Yingzhou Weile, Jochen Cote, Atina G Sun, Song Knapp, Jennifer Verby, Marta Roth, Frederick P Bioinformatics Applications Notes SUMMARY: The promise of personalized genomic medicine depends on our ability to assess the functional impact of rare sequence variation. Multiplexed assays can experimentally measure the functional impact of missense variants on a massive scale. However, even after such assays, many missense variants remain poorly measured. Here we describe a software pipeline and application to impute missing information in experimentally determined variant effect maps. AVAILABILITY AND IMPLEMENTATION: http://impute.varianteffect.org source code: https://github.com/joewuca/imputation. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2019-09-01 2019-01-14 /pmc/articles/PMC6735881/ /pubmed/30649215 http://dx.doi.org/10.1093/bioinformatics/btz012 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Wu, Yingzhou
Weile, Jochen
Cote, Atina G
Sun, Song
Knapp, Jennifer
Verby, Marta
Roth, Frederick P
A web application and service for imputing and visualizing missense variant effect maps
title A web application and service for imputing and visualizing missense variant effect maps
title_full A web application and service for imputing and visualizing missense variant effect maps
title_fullStr A web application and service for imputing and visualizing missense variant effect maps
title_full_unstemmed A web application and service for imputing and visualizing missense variant effect maps
title_short A web application and service for imputing and visualizing missense variant effect maps
title_sort web application and service for imputing and visualizing missense variant effect maps
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6735881/
https://www.ncbi.nlm.nih.gov/pubmed/30649215
http://dx.doi.org/10.1093/bioinformatics/btz012
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