Login / Signup

scShapes: a statistical framework for identifying distribution shapes in single-cell RNA-sequencing data.

Malindrie DharmaratneAmeya S KulkarniAtefeh Taherian FardJessica Cara Mar
Published in: GigaScience (2023)
This analysis also draws attention to genes that switch distribution shapes from a unimodal distribution to a zero-inflated distribution and raises open questions about the plausible biological mechanisms that may give rise to this, such as transcriptional bursting. Overall, the results from scShapes help to expand our understanding of the role that gene expression plays in the transcriptional regulation of a specific perturbation or cellular phenotype. Our framework scShapes is incorporated into a Bioconductor R package (https://www.bioconductor.org/packages/release/bioc/html/scShapes.html).
Keyphrases
  • gene expression
  • single cell
  • dna methylation
  • working memory
  • high throughput
  • machine learning
  • electronic health record
  • big data
  • artificial intelligence
  • data analysis