High-performance pipeline for MutMap and QTL-seq

SUMMARY: Bulked segregant analysis implemented in MutMap and QTL-seq is a powerful and efficient method to identify loci contributing to important phenotypic traits. However, the previous pipelines were not user-friendly to install and run. Here, we describe new pipelines for MutMap and QTL-seq. The...

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Autores principales: Sugihara, Yu, Young, Lester, Yaegashi, Hiroki, Natsume, Satoshi, Shea, Daniel J., Takagi, Hiroki, Booker, Helen, Innan, Hideki, Terauchi, Ryohei, Abe, Akira
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2022
Materias:
Bioinformatics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8935991/
https://www.ncbi.nlm.nih.gov/pubmed/35321412
http://dx.doi.org/10.7717/peerj.13170
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author Sugihara, Yu
Young, Lester
Yaegashi, Hiroki
Natsume, Satoshi
Shea, Daniel J.
Takagi, Hiroki
Booker, Helen
Innan, Hideki
Terauchi, Ryohei
Abe, Akira
author_facet Sugihara, Yu
Young, Lester
Yaegashi, Hiroki
Natsume, Satoshi
Shea, Daniel J.
Takagi, Hiroki
Booker, Helen
Innan, Hideki
Terauchi, Ryohei
Abe, Akira
author_sort Sugihara, Yu
collection PubMed
description SUMMARY: Bulked segregant analysis implemented in MutMap and QTL-seq is a powerful and efficient method to identify loci contributing to important phenotypic traits. However, the previous pipelines were not user-friendly to install and run. Here, we describe new pipelines for MutMap and QTL-seq. These updated pipelines are approximately 5–8 times faster than the previous pipeline, are easier for novice users to use, and can be easily installed through bioconda with all dependencies. AVAILABILITY: The new pipelines of MutMap and QTL-seq are written in Python and can be installed via bioconda. The source code and manuals are available online (MutMap: https://github.com/YuSugihara/MutMap, QTL-seq: https://github.com/YuSugihara/QTL-seq).
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spelling pubmed-89359912022-03-22 High-performance pipeline for MutMap and QTL-seq Sugihara, Yu Young, Lester Yaegashi, Hiroki Natsume, Satoshi Shea, Daniel J. Takagi, Hiroki Booker, Helen Innan, Hideki Terauchi, Ryohei Abe, Akira PeerJ Bioinformatics SUMMARY: Bulked segregant analysis implemented in MutMap and QTL-seq is a powerful and efficient method to identify loci contributing to important phenotypic traits. However, the previous pipelines were not user-friendly to install and run. Here, we describe new pipelines for MutMap and QTL-seq. These updated pipelines are approximately 5–8 times faster than the previous pipeline, are easier for novice users to use, and can be easily installed through bioconda with all dependencies. AVAILABILITY: The new pipelines of MutMap and QTL-seq are written in Python and can be installed via bioconda. The source code and manuals are available online (MutMap: https://github.com/YuSugihara/MutMap, QTL-seq: https://github.com/YuSugihara/QTL-seq). PeerJ Inc. 2022-03-18 /pmc/articles/PMC8935991/ /pubmed/35321412 http://dx.doi.org/10.7717/peerj.13170 Text en ©2022 Sugihara et al. 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 use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Sugihara, Yu
Young, Lester
Yaegashi, Hiroki
Natsume, Satoshi
Shea, Daniel J.
Takagi, Hiroki
Booker, Helen
Innan, Hideki
Terauchi, Ryohei
Abe, Akira
High-performance pipeline for MutMap and QTL-seq
title High-performance pipeline for MutMap and QTL-seq
title_full High-performance pipeline for MutMap and QTL-seq
title_fullStr High-performance pipeline for MutMap and QTL-seq
title_full_unstemmed High-performance pipeline for MutMap and QTL-seq
title_short High-performance pipeline for MutMap and QTL-seq
title_sort high-performance pipeline for mutmap and qtl-seq
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8935991/
https://www.ncbi.nlm.nih.gov/pubmed/35321412
http://dx.doi.org/10.7717/peerj.13170
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