SureTypeSC—a Random Forest and Gaussian mixture predictor of high confidence genotypes in single-cell data
Author(s) -
Ivan Vogel,
Robert Blanshard,
Eva R. Hoffmann
Publication year - 2019
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btz412
Subject(s) - genotyping , single nucleotide polymorphism , snp genotyping , genotype , snp , snp array , computer science , computational biology , genetics , biology , gene
Accurate genotyping of DNA from a single cell is required for applications such as de novo mutation detection, linkage analysis and lineage tracing. However, achieving high precision genotyping in the single-cell environment is challenging due to the errors caused by whole-genome amplification. Two factors make genotyping from single cells using single nucleotide polymorphism (SNP) arrays challenging. The lack of a comprehensive single-cell dataset with a reference genotype and the absence of genotyping tools specifically designed to detect noise from the whole-genome amplification step. Algorithms designed for bulk DNA genotyping cause significant data loss when used for single-cell applications.
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