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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Cytocipher determines significantly different populations of cells in single-cell RNA-seq data.

Brad Balderson¹, Michael Piper², Stefan Thor²

¹School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, QLD 4072, Australia.

Bioinformatics (Oxford, England)

|July 14, 2023

Summary

Cytocipher is a new bioinformatics tool that automatically identifies distinct cell clusters from single-cell RNA sequencing data. This method improves reproducibility and efficiency in cell type identification across various biological studies.

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Single-cell RNA sequencing (scRNA-seq) enables cell type identification in multicellular organisms.
Manual curation of scRNA-seq data for distinct cell clusters is time-consuming and prone to errors.

Purpose of the Study:

To develop a bioinformatics method and software package for statistically determining significant cell clusters from scRNA-seq data.
To improve the reproducibility and efficiency of scRNA-seq analysis.

Main Methods:

Development of Cytocipher, a scverse-compatible software package.
Statistical determination of transcriptionally distinct cell clusters.

Main Results:

Cytocipher successfully identified cell types in normal tissue, developmental, and disease datasets.
New cell types and subpopulations were identified, including CD8+ T cell subtypes and prostate cancer-associated luminal epithelial cells.
Cytocipher demonstrated scalability to large datasets, analyzing over 480,000 cells from the Tabula Sapiens Atlas.

Conclusions:

Cytocipher is a novel, generalizable method for statistically identifying reproducible cell clusters from scRNA-seq data.
The software package enhances biological insights across diverse research contexts.