Hypermut 3: Identifying specific mutational patterns in a defined nucleotide context that allows multistate characters.

Zena Lapp, Hyejin Yoon, Brian Foley, Thomas Leitner

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.

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0citing papers in PubMed

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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Hypermut 3: identifying specific mutational patterns in a defined nucleotide context that allows multistate characters.2025

5 · Who and what money

Authors and funding

4 authors.

Zena LappTheoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.ORCID 0000-0003-4674-2176

Hyejin YoonTheoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.

Brian FoleyTheoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.ORCID 0000-0002-1086-0296

Thomas LeitnerTheoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.ORCID 0000-0001-8160-2588

Funding

Reconstructing HIV Epidemics from HIV PhylogeneticsR01AI087520 · NIAID · TRIAD NATIONAL SECURITY, LLC · PI Thomas K. Leitner · 2010 to 2026

$11.2M

NIAID NIH HHS R01 AI087520

6 · The paper itself

Abstract

The detection of APOBEC3F- and APOBEC3G-induced mutations in virus sequences is useful for identifying hypermutated sequences. These sequences are not representative of viral evolution and can therefore alter the results of downstream sequence analyses if included. We previously published the software Hypermut, which detects hypermutation events in sequences relative to a reference. Two versions of this method are available as a webtool. Neither of these methods consider multistate characters or gaps in the sequence alignment. Here, we present an updated, user-friendly web and command-line version of Hypermut with functionality to handle multistate characters and gaps in the sequence alignment. This tool allows for straightforward integration of hypermutation detection into sequence analysis pipelines. As with the previous tool, while the main purpose is to identify G to A hypermutation events, any mutational pattern and context can be specified.

Identifiers

PMID39553937

DOI10.1101/2024.10.24.620069

PMCPMC11565710

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LicenceCC BY

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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.