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Random forest classifiers trained on simulated data enable accurate short read-based genotyping of structural variants in the alpha globin region at Chr16p13.3

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.11.27.568683Source: DataRank Database

Random forest classifiers trained on simulated data enable accurate short read-based genotyping of structural variants in the alpha globin region at Chr16p13.3 is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2023). On theSindex it has a DataRank of 0.

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Authors (11)

Xunde Wang,Mickias Tegegn,Zhi Liu ORCID,Mateus H. Gouveia ORCID,Gracelyn Hill ORCID

Live enrichment

PubMed:38076833 OpenAlex:https://openalex.org/W4389068665

National Institutes of Health

Grant: 1ZIAHL006233-03

Studies of the Natural History of Sickle Cell Disease

National Institutes of Health

Grant: 1ZIBHG000196-14

Inter- and Intra-Species Comparative Sequencing

National Institutes of Health

Grant: 1ZIAHG200362-06

Genetic epidemiology of complex diseases

greenLicense: http://creativecommons.org/publicdomain/zero/1.0/This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license (http://creativecommons.org/publicdomain/zero/1.0/) .

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2023/11/27/2023.11.27.568683.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2023.11.27.568683

repositoryhttp://dx.doi.org/10.1101/2023.11.27.568683

repositoryhttps://pubmed.ncbi.nlm.nih.gov/38076833

Fields of Study

Genomics and Rare DiseasesHemoglobinopathies and Related DisordersGenetic Associations and Epidemiology0206 medical engineering02 engineering and technology

Keywords

GenotypingLocus (genetics)GenotypeGeneticsBiologyComputational biologyPopulationComputer scienceArtificial intelligenceGeneMedicineArticle

Sustainable Development Goals

SDG 0: Life in Land