Assessing Inequality in Transcriptomic Data.
| Autor: | Jiang L; Howard Hughes Medical Institute, Boston Children's Hospital, Boston, MA 02115, USA; Program in Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA 02115, USA; Division of Hematology/Oncology, Department of Pediatrics, Boston Children's Hospital, Boston, MA 02115, USA., Tsoucas D; Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA., Yuan GC; Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. Electronic address: gcyuan@jimmy.harvard.edu. |
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| Jazyk: | angličtina |
| Zdroj: | Cell systems [Cell Syst] 2018 Feb 28; Vol. 6 (2), pp. 149-150. |
| DOI: | 10.1016/j.cels.2018.02.007 |
| Abstrakt: | Two studies in this issue of Cell Systems use the Gini index from economics to benchmark and quantify gene expression heterogeneity in single-cell or bulk RNA-seq datasets. (Copyright © 2018 Elsevier Inc. All rights reserved.) |
| Databáze: | MEDLINE |
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