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

Visualizations for genetic assignment analyses using the saddlepoint approximation method.

Biometrics - 1 Sept 2017

McMillan L F, Fewster R M

Abstract excerpt

We propose a method for visualizing genetic assignment data by characterizing the distribution of genetic profiles for each candidate source population. This method enhances the assignment method of Rannala and Mountain (1997) by calculating appropriate graph positions for individuals for which some genetic data are missing. An individual with missing data is positioned in the distributions of genetic profiles...

Read the complete abstract on PubMed

Topics

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

Share to Genetics, Population
Share to Genotype
Share to Microsatellite Repeats

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to New Zealand

Share to Software

Source

Identifiers

PMID: 28182851
DOI: 10.1111/biom.12667

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Visualizations for genetic assignment analyses using the saddlepoint approximation method.PMID 28182851Read ↗

Visualizing the geography of genetic variants.Semantic proximity Read ↗

Visualizing the Geography of Genetic VariantsSemantic proximity Read ↗

Revealing multi-scale population structure in large cohortsSemantic proximity Read ↗

Nonparametric approaches for population structure analysis.Semantic proximity Read ↗

AWclust: point-and-click software for non-parametric population structure analysis.Semantic proximity Read ↗

Inference and analysis of population structure using genetic data and network theorySemantic proximity Read ↗

SNP selection and multidimensional scaling to quantify population structure.Semantic proximity Read ↗

PopMLvis: a tool for analysis and visualization of population structure using genotype data from genome-wide association studies.Semantic proximity Read ↗

Estimation of spatial demographic maps from polymorphism data using a neural network.Semantic proximity Read ↗

Visualizing spatial population structure with estimated effective migration surfacesSemantic proximity Read ↗

A novel method for haplotype clustering and visualization.Semantic proximity Read ↗

A new individual-based spatial approach for identifying genetic discontinuities in natural populations.Semantic proximity Read ↗

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