Evidence map›Paper›PMID 29029186›Full record

ArticleMolecular biology and evolution2018

Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm.

Ha Minh Lam, Oliver Ratmann, Maciej F Boni

Open access · hybridAbstract read
In one paragraph

Article in Molecular biology and evolution, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 151 papers.

0numbers the graph read from it
0cells of the map it votes in
151citing papers in PubMed
4.4field-weighted citation impact, top 5% of its field
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

151 citing papers in PubMed, 233 citations in OpenAlex.

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  8. Population Genetic Study ofEcology and evolution · 2026
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  17. Molecular Characterization of EmergingInternational journal of molecular sciences · 2026
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  20. Biological causes and impacts of rugged tree landscapes in phylodynamic inference.Proceedings of the National Academy of Sciences of the United States of America · 2026
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91 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 3 countries.

Ha Minh LamWellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam.
Oliver RatmannMRC Centre for Outbreak Analyses and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Maciej F BoniWellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam.
Imperial College London · GBOxford University Clinical Research Unit · VNUniversity of Oxford · GB

Funding

Wellcome TrustWellcome Trust 089276/B/09/7Wellcome Trust 098511/Z/12/Z
6 · The paper itself

Abstract

Identifying recombinant sequences in an era of large genomic databases is challenging as it requires an efficient algorithm to identify candidate recombinants and parents, as well as appropriate statistical methods to correct for the large number of comparisons performed. In 2007, a computation was introduced for an exact nonparametric mosaicism statistic that gave high-precision P values for putative recombinants. This exact computation meant that multiple-comparisons corrected P values also had high precision, which is crucial when performing millions or billions of tests in large databases. Here, we introduce an improvement to the algorithmic complexity of this computation from O(mn3) to O(mn2), where m and n are the numbers of recombination-informative sites in the candidate recombinant. This new computation allows for recombination analysis to be performed in alignments with thousands of polymorphic sites. Benchmark runs are presented on viral genome sequence alignments, new features are introduced, and applications outside recombination analysis are discussed.

Indexed as

AlgorithmsGene RearrangementPhylogenyRecombination, GeneticSequence AlignmentSequence Analysis, DNASoftwaremosaic structurenonparametricrecombination

Identifiers

PMID29029186
PMCPMC5850291
OpenAlexW2762377150

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.