دورية أكاديمية
Consequences and opportunities arising due to sparser single-cell RNA-seq datasets.
| العنوان: | Consequences and opportunities arising due to sparser single-cell RNA-seq datasets. |
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| المؤلفون: | Bouland GA; Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.; Department of Human Genetics, Leiden University Medical Center, Leiden, 2333ZC, The Netherlands., Mahfouz A; Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands. a.mahfouz@lumc.nl.; Department of Human Genetics, Leiden University Medical Center, Leiden, 2333ZC, The Netherlands. a.mahfouz@lumc.nl.; Leiden Computational Biology Center, Leiden University Medical Center, Leiden, 2333ZC, The Netherlands. a.mahfouz@lumc.nl., Reinders MJT; Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands. m.j.t.reinders@tudelft.nl.; Department of Human Genetics, Leiden University Medical Center, Leiden, 2333ZC, The Netherlands. m.j.t.reinders@tudelft.nl.; Leiden Computational Biology Center, Leiden University Medical Center, Leiden, 2333ZC, The Netherlands. m.j.t.reinders@tudelft.nl. |
| المصدر: | Genome biology [Genome Biol] 2023 Apr 21; Vol. 24 (1), pp. 86. Date of Electronic Publication: 2023 Apr 21. |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: BioMed Central Ltd Country of Publication: England NLM ID: 100960660 Publication Model: Electronic Cited Medium: Internet ISSN: 1474-760X (Electronic) Linking ISSN: 14747596 NLM ISO Abbreviation: Genome Biol Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: London, UK : BioMed Central Ltd Original Publication: London : Genome Biology Ltd., c2000- |
| مواضيع طبية MeSH: | Software* , Gene Expression Profiling*/methods, Sequence Analysis, RNA/methods ; Single-Cell Gene Expression Analysis ; Single-Cell Analysis/methods ; Cluster Analysis |
| مستخلص: | With the number of cells measured in single-cell RNA sequencing (scRNA-seq) datasets increasing exponentially and concurrent increased sparsity due to more zero counts being measured for many genes, we demonstrate here that downstream analyses on binary-based gene expression give similar results as count-based analyses. Moreover, a binary representation scales up to ~ 50-fold more cells that can be analyzed using the same computational resources. We also highlight the possibilities provided by binarized scRNA-seq data. Development of specialized tools for bit-aware implementations of downstream analytical tasks will enable a more fine-grained resolution of biological heterogeneity. (© 2023. The Author(s).) |
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| تواريخ الأحداث: | Date Created: 20230421 Date Completed: 20230425 Latest Revision: 20230425 |
| رمز التحديث: | 20230426 |
| مُعرف محوري في PubMed: | PMC10120229 |
| DOI: | 10.1186/s13059-023-02933-w |
| PMID: | 37085823 |
| قاعدة البيانات: | MEDLINE |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 1474-760X |
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| DOI: | 10.1186/s13059-023-02933-w |