Read2Tree: scalable and accurate phylogenetic trees from raw reads.
Journal
bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187
Informations de publication
Date de publication:
13 Dec 2022
13 Dec 2022
Historique:
entrez:
23
12
2022
pubmed:
24
12
2022
medline:
24
12
2022
Statut:
epublish
Résumé
The inference of phylogenetic trees is foundational to biology. However, state-of-the-art phylogenomics requires running complex pipelines, at significant computational and labour costs, with additional constraints in sequencing coverage, assembly and annotation quality. To overcome these challenges, we present Read2Tree, which directly processes raw sequencing reads into groups of corresponding genes. In a benchmark encompassing a broad variety of datasets, our assembly-free approach was 10-100x faster than conventional approaches, and in most cases more accurate-the exception being when sequencing coverage was high and reference species very distant. To illustrate the broad applicability of the tool, we reconstructed a yeast tree of life of 435 species spanning 590 million years of evolution. Applied to
Identifiants
pubmed: 36561179
doi: 10.1101/2022.04.18.488678
pmc: PMC9774205
pii:
doi:
Types de publication
Preprint
Langues
eng
Subventions
Organisme : NIAID NIH HHS
ID : U19 AI144297
Pays : United States
Organisme : NHGRI NIH HHS
ID : UM1 HG008898
Pays : United States
Commentaires et corrections
Type : UpdateIn
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