Sensitive and error-tolerant annotation of protein-coding DNA with BATH.

Autor:	Krause GR; R. Ken Coit College of Pharmacy, University of Arizona, Tucson, AZ 85721, United States.; Department of Computer Science, University of Montana, Missoula, MT 59812, United States., Shands W; Department of Computer Science, University of Montana, Missoula, MT 59812, United States.; Genomics Institute, UC Santa Cruz, Santa Cruz, CA 95060, United States., Wheeler TJ; R. Ken Coit College of Pharmacy, University of Arizona, Tucson, AZ 85721, United States.; Department of Computer Science, University of Montana, Missoula, MT 59812, United States.
Jazyk:	angličtina
Zdroj:	Bioinformatics advances [Bioinform Adv] 2024 Jun 14; Vol. 4 (1), pp. vbae088. Date of Electronic Publication: 2024 Jun 14 (Print Publication: 2024).
DOI:	10.1093/bioadv/vbae088
Abstrakt:	Summary: We present BATH, a tool for highly sensitive annotation of protein-coding DNA based on direct alignment of that DNA to a database of protein sequences or profile hidden Markov models (pHMMs). BATH is built on top of the HMMER3 code base, and simplifies the annotation workflow for pHMM-based translated sequence annotation by providing a straightforward input interface and easy-to-interpret output. BATH also introduces novel frameshift-aware algorithms to detect frameshift-inducing nucleotide insertions and deletions (indels). BATH matches the accuracy of HMMER3 for annotation of sequences containing no errors, and produces superior accuracy to all tested tools for annotation of sequences containing nucleotide indels. These results suggest that BATH should be used when high annotation sensitivity is required, particularly when frameshift errors are expected to interrupt protein-coding regions, as is true with long-read sequencing data and in the context of pseudogenes. Availability and Implementation: The software is available at https://github.com/TravisWheelerLab/BATH. Competing Interests: None declared. (© The Author(s) 2024. Published by Oxford University Press.)
Databáze:	MEDLINE
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