Back to Search Start Over

hybpiper‐nf and paragone‐nf: Containerization and additional options for target capture assembly and paralog resolution

Authors :
Chris Jackson
Todd McLay
Alexander N. Schmidt‐Lebuhn
Source :
Applications in Plant Sciences, Vol 11, Iss 4, Pp n/a-n/a (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Abstract Premise The HybPiper pipeline has become one of the most widely used tools for the assembly of target capture data for phylogenomic analysis. After the production of locus sequences and before phylogenetic analysis, the identification of paralogs is a critical step for ensuring the accurate inference of evolutionary relationships. Algorithmic approaches using gene tree topologies for the inference of ortholog groups are computationally efficient and broadly applicable to non‐model organisms, especially in the absence of a known species tree. Methods and Results We containerized and expanded the functionality of both HybPiper and a pipeline for the inference of ortholog groups, providing novel options for the treatment of target capture sequence data, and allowing seamless use of the outputs of the former as inputs for the latter. The Singularity container presented here includes all dependencies, and the corresponding pipelines (hybpiper‐nf and paragone‐nf, respectively) are implemented via two Nextflow scripts for easier deployment and to vastly reduce the number of commands required for their use. Conclusions The hybpiper‐nf and paragone‐nf pipelines are easily installed and provide a user‐friendly experience and robust results to the phylogenetic community. They are used by the Australian Angiosperm Tree of Life project. The pipelines are available at https://github.com/chrisjackson-pellicle/hybpiper-nf and https://github.com/chrisjackson-pellicle/paragone-nf.

Details

Language :
English
ISSN :
21680450
Volume :
11
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Applications in Plant Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.2133dfefccf54dc896d27d2aec2e87e9
Document Type :
article
Full Text :
https://doi.org/10.1002/aps3.11532