COMSE: analysis of single-cell RNA-seq data using community detection-based feature selection.
Qinhuan LuoYaozhu ChenXun LanPublished in: BMC biology (2024)
COMSE provides an efficient unsupervised framework that selects highly informative genes in scRNA-seq data improving cell sub-states identification and cell clustering. It identifies gene subsets that reveal biological and technical heterogeneity, supporting applications like batch effect correction and pathway analysis. It also provides robust results for bulk RNA-seq data analysis.
Keyphrases
- single cell
- rna seq
- data analysis
- genome wide
- high throughput
- machine learning
- electronic health record
- healthcare
- big data
- mental health
- copy number
- gene expression
- dna methylation
- stem cells
- deep learning
- mesenchymal stem cells
- artificial intelligence
- genome wide identification
- bone marrow
- cell therapy
- sensitive detection