Metacells untangle large and complex single-cell transcriptome networks
Published inBMC bioinformatics, vol. 23, no. 1, 336
First online date2022-08-13
Abstract
Keywords
- Coarse-graining
- Computational biology
- Metacells
- Single-cell transcriptomics
- COVID-19
- Cluster Analysis
- Humans
- Sequence Analysis, RNA / methods
- Single-Cell Analysis / methods
- Transcriptome
Funding
- Swiss National Science Fondation - Computational biology analyses to characterize immune cell infiltrations in the tumor micro-environment using bulk and single-cell gene expression data [31003A_173156]
Citation (ISO format)
BILOUS, Mariia et al. Metacells untangle large and complex single-cell transcriptome networks. In: BMC bioinformatics, 2022, vol. 23, n° 1, p. 336. doi: 10.1186/s12859-022-04861-1
Main files (1)
Article (Published version)
Secondary files (1)
Identifiers
- PID : unige:164698
- DOI : 10.1186/s12859-022-04861-1
- PMID : 35963997
- PMCID : PMC9375201
Datasets
- https://github.com/GfellerLab/SuperCell
- https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE118767
- https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE127465
- https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE116390
- https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE95315
- https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM3852755
- https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE158055
- https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE154763
- https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE60424
- https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE86337
- https://doi.org/10.5281/zenodo.5048449
ISSN of the journal1471-2105