IMMerge: merging imputation data at scale

SUMMARY: Genomic data are often processed in batches and analyzed together to save time. However, it is challenging to combine multiple large VCFs and properly handle imputation quality and missing variants due to the limitations of available tools. To address these concerns, we developed IMMerge, a...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhu, Wanying, Chen, Hung-Hsin, Petty, Alexander S, Petty, Lauren E, Polikowsky, Hannah G, Gamazon, Eric R, Below, Jennifer E, Highland, Heather M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Applications Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9805583/
https://www.ncbi.nlm.nih.gov/pubmed/36413071
http://dx.doi.org/10.1093/bioinformatics/btac750
_version_ 1784862358956408832
author Zhu, Wanying
Chen, Hung-Hsin
Petty, Alexander S
Petty, Lauren E
Polikowsky, Hannah G
Gamazon, Eric R
Below, Jennifer E
Highland, Heather M
author_facet Zhu, Wanying
Chen, Hung-Hsin
Petty, Alexander S
Petty, Lauren E
Polikowsky, Hannah G
Gamazon, Eric R
Below, Jennifer E
Highland, Heather M
author_sort Zhu, Wanying
collection PubMed
description SUMMARY: Genomic data are often processed in batches and analyzed together to save time. However, it is challenging to combine multiple large VCFs and properly handle imputation quality and missing variants due to the limitations of available tools. To address these concerns, we developed IMMerge, a Python-based tool that takes advantage of multiprocessing to reduce running time. For the first time in a publicly available tool, imputation quality scores are correctly combined with Fisher’s z transformation. AVAILABILITY AND IMPLEMENTATION: IMMerge is an open-source project under MIT license. Source code and user manual are available at https://github.com/belowlab/IMMerge.
format Online
Article
Text
id pubmed-9805583
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-98055832023-01-03 IMMerge: merging imputation data at scale Zhu, Wanying Chen, Hung-Hsin Petty, Alexander S Petty, Lauren E Polikowsky, Hannah G Gamazon, Eric R Below, Jennifer E Highland, Heather M Bioinformatics Applications Note SUMMARY: Genomic data are often processed in batches and analyzed together to save time. However, it is challenging to combine multiple large VCFs and properly handle imputation quality and missing variants due to the limitations of available tools. To address these concerns, we developed IMMerge, a Python-based tool that takes advantage of multiprocessing to reduce running time. For the first time in a publicly available tool, imputation quality scores are correctly combined with Fisher’s z transformation. AVAILABILITY AND IMPLEMENTATION: IMMerge is an open-source project under MIT license. Source code and user manual are available at https://github.com/belowlab/IMMerge. Oxford University Press 2022-11-22 /pmc/articles/PMC9805583/ /pubmed/36413071 http://dx.doi.org/10.1093/bioinformatics/btac750 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://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 Note
Zhu, Wanying
Chen, Hung-Hsin
Petty, Alexander S
Petty, Lauren E
Polikowsky, Hannah G
Gamazon, Eric R
Below, Jennifer E
Highland, Heather M
IMMerge: merging imputation data at scale
title IMMerge: merging imputation data at scale
title_full IMMerge: merging imputation data at scale
title_fullStr IMMerge: merging imputation data at scale
title_full_unstemmed IMMerge: merging imputation data at scale
title_short IMMerge: merging imputation data at scale
title_sort immerge: merging imputation data at scale
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9805583/
https://www.ncbi.nlm.nih.gov/pubmed/36413071
http://dx.doi.org/10.1093/bioinformatics/btac750
work_keys_str_mv AT zhuwanying immergemergingimputationdataatscale
AT chenhunghsin immergemergingimputationdataatscale
AT pettyalexanders immergemergingimputationdataatscale
AT pettylaurene immergemergingimputationdataatscale
AT polikowskyhannahg immergemergingimputationdataatscale
AT gamazonericr immergemergingimputationdataatscale
AT belowjennifere immergemergingimputationdataatscale
AT highlandheatherm immergemergingimputationdataatscale

Ejemplares similares