Cluster Buster: A Machine Learning Algorithm for Genotyping SNPs from Raw Data

Abstract excerpt

Genotyping single nucleotide polymorphisms (SNPs) is fundamental to disease research, as researchers seek to establish links between genetic variation and disease. Although significant advances in genome technology have been made with the development of bead-based SNP genotyping and Genome Studio software, some SNPs still fail to be genotyped, resulting in “no-calls” that impede downstream analyses. To recover the...

Topics

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• Alleles
• Costs and Cost Analysis
• Genetic Association Studies
• Genetic Predisposition to Disease
• Genetic Variation
• Genotyping Techniques
• Neurodegenerative Diseases
• Oligonucleotide Array Sequence Analysis

Identifiers and source

Literature Corpus work

23b2f7fa-1c98-52df-af2f-3a5d8daab68c

DOI

10.1101/2024.08.23.609429