Article

A deep learning framework for characterization of genotype data

2020-10-02

Abstract excerpt

<h4>ABSTRACT</h4> Dimensionality reduction is a data transformation technique widely used in various fields of genomics research. The application of dimensionality reduction to genotype data is known to capture genetic similarity between individuals, and is used for visualization of genetic variation, identification of population structure as well as ancestry mapping. Among frequently used methods are PCA, which...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 38ce0ee3-3ae1-583a-9ff6-281fd45dc925
DOI: 10.1101/2020.09.30.320994

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A deep learning framework for characterization of genotype dataDOI 10.1101/2020.09.30.320994Read

A deep learning framework for characterization of genotype data.Semantic proximity Read

Dimensionality reduction of genetic data using contrastive learning.Semantic proximity Read

Dimensionality Reduction of Genetic Data using Contrastive LearningSemantic proximity Read

Hybrid Autoencoder with Orthogonal Latent Space for Robust Population Structure InferenceSemantic proximity Read

Hyperbolic geometry-based deep learning methods to produce population trees from genotype dataSemantic proximity Read

Autoencoders for genomic variation analysis.Semantic proximity Read

Computing Linkage Disequilibrium Aware Genome Embeddings using AutoencodersSemantic proximity Read

Deep Variational Autoencoders for Population GeneticsSemantic proximity Read

Deep Variational Autoencoders for Population GeneticsSemantic proximity Read

Revealing multi-scale population structure in large cohortsSemantic proximity Read

Exploration of deep-learning based classification with human SNP image graphsSemantic proximity Read

Highlighting nonlinear patterns in population genetics datasets.Semantic proximity Read