Evidence map›Paper›PMID 37775806›Full record

ArticleAlgorithms for molecular biology : AMB2023

Constructing founder sets under allelic and non-allelic homologous recombination.

Konstantinn Bonnet, Tobias Marschall, Daniel Doerr

Erratum issuedAbstract read
In one paragraph

Article in Algorithms for molecular biology : AMB, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Konstantinn BonnetInstitute for Medical Biometry and Bioinformatics, Medical Faculty, and Center for Digital Medicine, Heinrich Heine University, Moorenstr. 5, 40225, Düsseldorf, Germany.
Tobias MarschallInstitute for Medical Biometry and Bioinformatics, Medical Faculty, and Center for Digital Medicine, Heinrich Heine University, Moorenstr. 5, 40225, Düsseldorf, Germany. tobias.marschall@hhu.de.
Daniel DoerrInstitute for Medical Biometry and Bioinformatics, Medical Faculty, and Center for Digital Medicine, Heinrich Heine University, Moorenstr. 5, 40225, Düsseldorf, Germany. daniel.doerr@hhu.de.

Funding

Representing structural haplotypes and complex genetic variation in pan-genome graphsU01HG010973 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHAISSON, MARK, EICHLER, EVAN · 2020 to 2023
$1.3M
NHGRI NIH HHS U01 HG010973NIH HHS 1U01HG010973
6 · The paper itself

Abstract

Homologous recombination between the maternal and paternal copies of a chromosome is a key mechanism for human inheritance and shapes population genetic properties of our species. However, a similar mechanism can also act between different copies of the same sequence, then called non-allelic homologous recombination (NAHR). This process can result in genomic rearrangements-including deletion, duplication, and inversion-and is underlying many genomic disorders. Despite its importance for genome evolution and disease, there is a lack of computational models to study genomic loci prone to NAHR. In this work, we propose such a computational model, providing a unified framework for both (allelic) homologous recombination and NAHR. Our model represents a set of genomes as a graph, where haplotypes correspond to walks through this graph. We formulate two founder set problems under our recombination model, provide flow-based algorithms for their solution, describe exact methods to characterize the number of recombinations, and demonstrate scalability to problem instances arising in practice.

Indexed as

Founder set reconstructionHomologous recombinationNAHRPangenomicsVariation graph

Identifiers

PMID37775806
PMCPMC10543304

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.