Application of information theoretical approaches to assess diversity and similarity in single-cell transcriptomics
| Autor: | Maciej Pietrzak, Michał T. Seweryn, Qin Ma |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Single cell transcriptomics media_common.quotation_subject lcsh:Biotechnology Biophysics Computational biology Information theory Biochemistry Renyi’s entropy Transcriptome 03 medical and health sciences 0302 clinical medicine Similarity (network science) Structural Biology lcsh:TP248.13-248.65 Genetics Cluster analysis 030304 developmental biology media_common Renyi’s divergence 0303 health sciences Single cell sequencing Diversity and similarity assessment Short Review Computer Science Applications 030220 oncology & carcinogenesis Identification (biology) human activities Biotechnology Diversity (politics) |
| Zdroj: | Computational and Structural Biotechnology Journal Computational and Structural Biotechnology Journal, Vol 18, Iss, Pp 1830-1837 (2020) |
| ISSN: | 2001-0370 |
| Popis: | Single-cell transcriptomics offers a powerful way to reveal the heterogeneity of individual cells. To date, many information theoretical approaches have been proposed to assess diversity and similarity, and characterize the latent heterogeneity in transcriptome data. Diversity implies gene expression variations and can facilitate the identification of signature genes; while, similarity unravels co-expression patterns for cell type clustering. In this review, we summarized 16 measures of information theory used for evaluating diversity and similarity in single-cell transcriptomic data, provide references and shed light on selected theoretical properties when there is a need to select proper measurements in general cases. We further provide an R package assembling discussed approaches to improve the researchers own single-cell transcriptome study. At last, we prospected further applications of diversity and similarity measures in support of depicting heterogeneity in single-cell multi-omics data. |
| Databáze: | OpenAIRE |
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