Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Estimating gene conversion rates from population data using multi-individual identity by descent.

American journal of human genetics - 4 Sept 2025

Browning Sharon R, Browning Brian L

Abstract excerpt

In humans, homologous gene conversions occur at a higher rate than crossovers; however, gene conversion tracts are small and often unobservable. As a result, estimating gene conversion rates is more difficult than estimating crossover rates. We present a method for multi-individual identity-by-descent (IBD) inference that allows for mismatches due to genotype error and gene conversion. We use the inferred IBD to...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Alleles
Share to Crossing Over, Genetic
Share to Gene Conversion

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genetics, Population

Share to Genotype

Share to Models, Genetic

Source

Open in PubMed Open full text

Identifiers

PMID: 40848714
DOI: 10.1016/j.ajhg.2025.07.019
PMCID: PMC12380118

Genes

PRDM9

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Estimating gene conversion rates from population data using multi-individual identity by descent.PMID 40848714Read ↗

Estimating gene conversion rates from population data using multi-individual identity by descentSemantic proximity Read ↗

Biobank-scale inference of multi-individual identity by descent and gene conversion.Semantic proximity Read ↗

Insights into gene conversion and crossing-over processes from long-read sequencing of human, chimpanzee and gorilla testes and spermSemantic proximity Read ↗

Modeling the length distribution of gene conversion tracts in humans from the UK Biobank sequence dataSemantic proximity Read ↗

Insights into non-crossover recombination from long-read sperm sequencingSemantic proximity Read ↗

Non-crossover gene conversions show strong GC bias and unexpected clustering in humansSemantic proximity Read ↗

The rate of meiotic gene conversion varies by sex and age.Semantic proximity Read ↗

Estimating meiotic gene conversion rates from population genetic data.Semantic proximity Read ↗

Non-crossover gene conversions show strong GC bias and unexpected clustering in humans.Semantic proximity Read ↗

Estimating the genome-wide mutation rate from thousands of unrelated individuals.Semantic proximity Read ↗

Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences.Semantic proximity Read ↗

Rare variant enriched identity-by-descent enables the detection of distant relatedness and older divergence between populationsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.