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Protocols

SC3 specifications

Information


Unique identifier OMICS_11110
Name SC3
Alternative name Single-Cell Consensus Clustering
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages C++, R
License GNU General Public License version 3.0
Computer skills Advanced
Stability Stable
Maintained Yes

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Documentation


Maintainer


  • person_outline Vladimir Kiselev

Publication for Single-Cell Consensus Clustering

SC3 citations

 (19)
library_books

Single Cell Multi Omics Technology: Methodology and Application

2018
PMCID: 5919954
PMID: 29732369
DOI: 10.3389/fcell.2018.00028

[…] ple, tools based on different theoretical frameworks have been developed to cluster cells based on their gene expression similarity, such as SINCERA (Guo et al., ), pcaReduce (Žurauskiene and Yau, ), SC3 (Kiselev et al., ), and SNN-Cliq (Xu and Su, ). Additional tools have been developed to reconstruct cell lineage by ordering cells according to computationally inferred pseudo-time (Trapnell et al […]

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

[…] number of clusters for comparison with other methods. The reported result of Seurat is computed with the resolution parameter that gives the exact number of clusters and the lowest error.To apply the SC3 [] we downloaded SC3 v1.7.2 R package from Bioconductor. All parameters in SC3 are set to default. In the experiments with more than 5000 instances for clustering, the SVM mode will be trigged to […]

call_split

Single cell RNA sequencing reveals developmental heterogeneity of blastomeres during major genome activation in bovine embryos

2018
Sci Rep
PMCID: 5840315
PMID: 29511234
DOI: 10.1038/s41598-018-22248-2
call_split See protocol

[…] Two unsupervised hierarchical clustering analyses were performed on the filtered and normalised data. In order to investigate the transcripts in single cells, Single-Cell Consensus Clustering (SC3) version 1.4.2, R package was used. The required number of clusters was calculated after testing the significance of the eigenvalues of the matrix of covariance, […]

call_split

Clonally diverse CD38+HLA DR+CD8+ T cells persist during fatal H7N9 disease

2018
Nat Commun
PMCID: 5827521
PMID: 29483513
DOI: 10.1038/s41467-018-03243-7
call_split See protocol

[…] 2.1); more specifically CuffQuant was used to calculate FPKM and CuffNorm to normalize the FPKM values based on total mRNA content. Unsupervised hierarchical clustering was performed with the package SC3. Heatmaps were generated with the R package made4 and pheatmap. SC3 package in R was utilized for clustering analysis, and to identify differentially expressed genes across clusters. This package […]

library_books

Massively Parallel Single Nucleus Transcriptional Profiling Defines Spinal Cord Neurons and Their Activity during Behavior

2018
Cell Rep
PMCID: 5849084
PMID: 29466745
DOI: 10.1016/j.celrep.2018.02.003

[…] other in the center of the plot, with deep dorsal and intermediate clusters between (). Similarly, dorsal clusters were generally present as homogeneous blocks in a cell consensus matrix and had high SC3 silhouette width consensus values (a measure that represents the diagonality of the matrix), while ventral clusters showed inter-relatedness with other ventral clusters and had low silhouette widt […]

library_books

Exploring the Complexity of Cortical Development Using Single Cell Transcriptomics

2018
Front Neurosci
PMCID: 5801402
PMID: 29456488
DOI: 10.3389/fnins.2018.00031

[…] (PCA) and t-SNE to obtain the overview and structure of subpopulations (Poirion et al., ). For the unsupervised clustering, ConsensusClusterPlus R (Wilkerson and Hayes, ), EMCluster (Jung et al., ), SC3 (Kiselev et al., ), SNN-Cliq (Xu and Su, ), SCUBA (Marco et al., ), BackSPIN (Zeisel et al., ), and PAGODA (Fan et al., ) provide methods to identify the subpopulation from the single-cell transcr […]

Citations

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SC3 institution(s)
Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK; Cambridge Institute for Medical Research, Wellcome Trust/MRC Stem Cell Institute, University of Cambridge, Cambridge, UK; Department of Haematology, University of Cambridge, Cambridge, UK; Department of Mathematics and naXys, University of Namur, Belgium; ICTEAM, Université catholique de Louvain, Belgium; Epigenetics Programme, The Babraham Institute, Babraham, Cambridge, UK; EMBL¬European Bioinformatics Institute, Hinxton, Cambridge, UK; Centre for Throphoblast Research, University of Cambridge, Cambridge, UK; Department of Mathematics, Imperial College London, London, UK

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