Evidence map›Paper›PMID 38260252›Full record

ArticlebioRxiv : the preprint server for biology2024

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

Genevieve R Krause, Walt Shands, Travis J Wheeler

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Genevieve R KrauseR. Ken Coit College of Pharmacy, University of Arizona, Tucson, Arizona, USA.
Walt ShandsDepartment of Computer Science, University of Montana, Missoula, Montana, USA.
Travis J WheelerR. Ken Coit College of Pharmacy, University of Arizona, Tucson, Arizona, USA.ORCID 0000-0003-2004-1785

Funding

Surveillance genome sequencing to detect SARS-CoV-2 virus variants in MontanaP20GM103546 · NIGMS · UNIVERSITY OF MONTANA · PI BOWLER, BRUCE E · 2012 to 2021
$19.2M
Dfam: sustainable growth, curation support, and improved quality for mobile element annotationU24HG010136 · NHGRI · INSTITUTE FOR SYSTEMS BIOLOGY · PI Robert MacDonald Hubley, Arian Fredericus Anthonius Smit · 2018 to 2026
$5.2M
Machine learning approaches for improved accuracy and speed in sequence annotation: supplement for software enhancementR01GM132600 · NIGMS · UNIVERSITY OF MONTANA · PI WHEELER, TRAVIS JOHN · 2019 to 2022
$1.4M
NHGRI NIH HHS U24 HG010136NIGMS NIH HHS P20 GM103546NIGMS NIH HHS R01 GM132600
6 · The paper itself

Abstract

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 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.

Indexed as

Frameshift MutationsGenome AnnotationProfile Hidden Markov ModelsSequence Alignment

Identifiers

PMID38260252
PMCPMC10802276

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.