scAnnotatR: framework to accurately classify cell types in single-cell RNA-sequencing data. | BMC Bioinformatics;23(1): 44, 2022 Jan 17. | MEDLINE

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scAnnotatR: framework to accurately classify cell types in single-cell RNA-sequencing data.

Nguyen, Vy; Griss, Johannes.

Affiliation

Nguyen V; Department of Dermatology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
Griss J; Department of Dermatology, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria. johannes.griss@meduniwien.ac.at.

BMC Bioinformatics ; 23(1): 44, 2022 Jan 17.

Article in En | MEDLINE | ID: mdl-35038984

Subject(s)
Key words

Bioconductor; Cell classification; Machine learning; R; SVM; scAnnotatR; scRNAseq

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: RNA / Single-Cell Analysis Language: En Journal: BMC Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2022 Document type: Article Affiliation country:

Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: RNA / Single-Cell Analysis Language: En Journal: BMC Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2022 Document type: Article Affiliation country: