Decoding the building blocks of cellular processes from single-cell transcriptomics data

Most features of a cell are determined by gene programs — sets of co-expressed genes that execute a specific function. By incorporating existing knowledge about gene programs and cell types, the Spectra factor analysis method improves how we decode single-cell transcriptomic data and offers insights...

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Bibliographic Details
Published in:Nature biotechnology 2024-07, Vol.42 (7), p.1034-1035
Format: Article
Language:English
Subjects:
631/114/129/2043
631/114/1305
631/114/2114
631/114/2397
Agriculture
Bioinformatics
Biology
Biomedical and Life Sciences
Biomedical Engineering/Biotechnology
Biomedicine
Biotechnology
Breast cancer
Computational Biology - methods
Cytotoxicity
Datasets
Decoding
Discriminant analysis
DNA methylation
Factor analysis
Gene expression
Gene Expression Profiling - methods
Humans
Immunology
Immunotherapy
Life Sciences
Lymphocytes
Methods
Patients
Research Briefing
Single-Cell Analysis - methods
Transcriptome - genetics
Transcriptomics
Tumors
Citations: Items that this one cites
Online Access:Get full text
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Description
Summary:Most features of a cell are determined by gene programs — sets of co-expressed genes that execute a specific function. By incorporating existing knowledge about gene programs and cell types, the Spectra factor analysis method improves how we decode single-cell transcriptomic data and offers insights into challenging tumor immune contexts.
ISSN:1087-0156
1546-1696
1546-1696
DOI:10.1038/s41587-023-01967-6