JOE R. DELANEY*
BIOCELL, Vol.45, No.5, pp. 1167-1170, 2021, DOI:10.32604/biocell.2021.017296
- 12 July 2021
Abstract Single-cell sequencing data has transformed the understanding of biological heterogeneity. While many flavors
of single-cell sequencing have been developed, single-cell RNA sequencing (scRNA-seq) is currently the most prolific
form in published literature. Bioinformatic analysis of differential biology within the population of cells studied relies
on inferences and grouping of cells due to the spotty nature of data within individual cell scRNA-seq gene counts.
One biologically relevant variable is readily inferred from scRNA-seq gene count tables regardless of individual gene
representation within single cells: aneuploidy. Since hundreds of genes are present on chromosome arms, high-quality
inferences More >
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