scVDMC specifications

Information


Unique identifier OMICS_28607
Name scVDMC
Alternative name single cell Variance-Driven Multitask Clustering
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages MATLAB, Octave
License Apache License version 2.0
Computer skills Advanced
Stability Stable
Maintained Yes

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Versioning


No version available

Maintainers


  • person_outline Rui Kuang
  • person_outline Jakub Tolar

Publication for single cell Variance-Driven Multitask Clustering

scVDMC citation

library_books

A multitask clustering approach for single cell RNA seq analysis in Recessive Dystrophic Epidermolysis Bullosa

2018
PLoS Comput Biol
PMCID: 5908193
PMID: 29630593
DOI: 10.1371/journal.pcbi.1006053

[…] scVDMC was compared with six baseline methods: (1) k-means clustering on each domain separately, (2) pooling all domains and applying k-means clustering, (3) SNN-Cliq [], (4) CellTree [], (5) Seurat [ […]

scVDMC institution(s)
Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA; Department of Genetics, Cell Biology and Development, University of Minnesota Twin Cities, Minneapolis, MN, USA; Minnesota Supercomputing Institute, University of Minnesota Twin Cities, Minneapolis, MN, USA; Department of Pediatrics, University of Minnesota Twin Cities, Minneapolis, MN, USA
scVDMC funding source(s)
Supported by a grant from the National Science Foundations, USA (NSF III 1149697), the CAPES Foundation, Ministry of Education of Brazil (BEX 13250/13-2), the National Institutes of Health, USA (NIH T32GM113846), the National Institutes of Health, USA (R01 AR063070).

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