Related Experiment Video
Updated: Jul 2, 2025
10:12
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
Published on: January 10, 2019
18.5K
Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data
Chibuikem Nwizu1,2, Madeline Hughes3, Michelle L Ramseier4,5,6,7,8
1Center for Computational Molecular Biology, Brown University, Providence, RI, USA.
Biorxiv : the Preprint Server for Biology
|February 26, 2024
Summary
NCLUSION is a new method for single-cell RNA sequencing (scRNA-seq) analysis that simultaneously clusters cells and identifies marker genes. This approach reduces runtime and improves the biological relevance of findings in cellular heterogeneity studies.
Area of Science:
- Computational biology
- Genomics
- Bioinformatics
Background:
- Single-cell RNA sequencing (scRNA-seq) is crucial for understanding cellular heterogeneity.
- Current clustering methods require manual parameter tuning and rely on potentially unreliable differential expression analysis for marker identification.
Conclusions:
- NCLUSION offers a reliable and efficient tool for scRNA-seq data analysis.
- Facilitates hypothesis generation for understanding gene expression variation in cell populations.
- Advances the characterization of cellular heterogeneity through integrated clustering and marker discovery.
