TreeTuner: A pipeline for minimizing redundancy and complexity in large phylogenetic datasets

Xi Zhang; Yining Hu; Laura Eme; Shinichiro Maruyama; Robert J.M. Eveleigh; Bruce A. Curtis; Shannon J. Sibbald; Julia F. Hopkins; Gina V. Filloramo; Klaas J. van Wijk; John M. Archibald

doi:10.1016/j.xpro.2022.101175

TreeTuner: A pipeline for minimizing redundancy and complexity in large phylogenetic datasets

Xi Zhang, Yining Hu, Laura Eme, Shinichiro Maruyama, Robert J.M. Eveleigh, Bruce A. Curtis, Shannon J. Sibbald, Julia F. Hopkins, Gina V. Filloramo, Klaas J. van Wijk, John M. Archibald

Research output: Contribution to journal › Article › peer-review

Abstract

Various bioinformatics protocols have been developed for trimming the number of operational taxonomic units (OTUs) in phylogenetic datasets, but they typically require significant manual intervention. Here we present TreeTuner, a semiautomated pipeline that allows both coarse and fine-scale tuning of large protein sequence phylogenetic datasets via the minimization of OTU redundancy. TreeTuner facilitates preliminary investigation of such datasets as well as more rigorous downstream analysis of specific subsets of OTUs. For complete details on the use and execution of this protocol, please refer to Maruyama et al. (2013) and Sibbald et al. (2019).

Original language	English
Article number	101175
Journal	STAR Protocols
Volume	3
Issue number	1
DOIs	https://doi.org/10.1016/j.xpro.2022.101175
Publication status	Published - 2022 Mar 18
Externally published	Yes

Keywords

Bioinformatics
Evolutionary biology
Genomics
Systems biology

ASJC Scopus subject areas

Neuroscience(all)
Biochemistry, Genetics and Molecular Biology(all)
Immunology and Microbiology(all)

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10.1016/j.xpro.2022.101175

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title = "TreeTuner: A pipeline for minimizing redundancy and complexity in large phylogenetic datasets",

abstract = "Various bioinformatics protocols have been developed for trimming the number of operational taxonomic units (OTUs) in phylogenetic datasets, but they typically require significant manual intervention. Here we present TreeTuner, a semiautomated pipeline that allows both coarse and fine-scale tuning of large protein sequence phylogenetic datasets via the minimization of OTU redundancy. TreeTuner facilitates preliminary investigation of such datasets as well as more rigorous downstream analysis of specific subsets of OTUs. For complete details on the use and execution of this protocol, please refer to Maruyama et al. (2013) and Sibbald et al. (2019).",

keywords = "Bioinformatics, Evolutionary biology, Genomics, Systems biology",

author = "Xi Zhang and Yining Hu and Laura Eme and Shinichiro Maruyama and Eveleigh, {Robert J.M.} and Curtis, {Bruce A.} and Sibbald, {Shannon J.} and Hopkins, {Julia F.} and Filloramo, {Gina V.} and {van Wijk}, {Klaas J.} and Archibald, {John M.}",

note = "Funding Information: This work was supported by a Gordon and Betty Moore Foundation grant ( GBMF5782 ) and by a Discovery Grant from the Natural Sciences and Engineering Research Council of Canada ( RGPIN-2019-05058 ), both awarded to J.M.A. We thank all authors of the papers that were cited in this manuscript. We also thank the editors and reviewers for their helpful comments on an earlier version of this manuscript. Publisher Copyright: {\textcopyright} 2022 The Author(s)",

year = "2022",

month = mar,

day = "18",

doi = "10.1016/j.xpro.2022.101175",

language = "English",

volume = "3",

journal = "STAR Protocols",

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T2 - A pipeline for minimizing redundancy and complexity in large phylogenetic datasets

AU - Zhang, Xi

AU - Hu, Yining

AU - Eme, Laura

AU - Maruyama, Shinichiro

AU - Eveleigh, Robert J.M.

AU - Curtis, Bruce A.

AU - Sibbald, Shannon J.

AU - Hopkins, Julia F.

AU - Filloramo, Gina V.

AU - van Wijk, Klaas J.

AU - Archibald, John M.

N1 - Funding Information: This work was supported by a Gordon and Betty Moore Foundation grant ( GBMF5782 ) and by a Discovery Grant from the Natural Sciences and Engineering Research Council of Canada ( RGPIN-2019-05058 ), both awarded to J.M.A. We thank all authors of the papers that were cited in this manuscript. We also thank the editors and reviewers for their helpful comments on an earlier version of this manuscript. Publisher Copyright: © 2022 The Author(s)

PY - 2022/3/18

Y1 - 2022/3/18

N2 - Various bioinformatics protocols have been developed for trimming the number of operational taxonomic units (OTUs) in phylogenetic datasets, but they typically require significant manual intervention. Here we present TreeTuner, a semiautomated pipeline that allows both coarse and fine-scale tuning of large protein sequence phylogenetic datasets via the minimization of OTU redundancy. TreeTuner facilitates preliminary investigation of such datasets as well as more rigorous downstream analysis of specific subsets of OTUs. For complete details on the use and execution of this protocol, please refer to Maruyama et al. (2013) and Sibbald et al. (2019).

AB - Various bioinformatics protocols have been developed for trimming the number of operational taxonomic units (OTUs) in phylogenetic datasets, but they typically require significant manual intervention. Here we present TreeTuner, a semiautomated pipeline that allows both coarse and fine-scale tuning of large protein sequence phylogenetic datasets via the minimization of OTU redundancy. TreeTuner facilitates preliminary investigation of such datasets as well as more rigorous downstream analysis of specific subsets of OTUs. For complete details on the use and execution of this protocol, please refer to Maruyama et al. (2013) and Sibbald et al. (2019).

KW - Bioinformatics

KW - Evolutionary biology

KW - Genomics

KW - Systems biology

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JO - STAR Protocols

JF - STAR Protocols

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ER -

TreeTuner: A pipeline for minimizing redundancy and complexity in large phylogenetic datasets

Abstract

Keywords

ASJC Scopus subject areas

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