RCA specifications


Unique identifier OMICS_18061
Name RCA
Alternative name Reference Component Analysis
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages R
License MIT License
Computer skills Advanced
Version 1.0
Stability Stable
Maintained Yes




No version available


  • person_outline Iain Beehuat Tan

Publication for Reference Component Analysis

RCA citation


Next generation sequencing traces human induced pluripotent stem cell lines clonally generated from heterogeneous cancer tissue

PMCID: 5440771
PMID: 28596815
DOI: 10.4252/wjsc.v9.i5.77

[…] es demonstrated differences derived from their distinct starting tissues and similarity and heterogeneity derived from their common starting heterogeneous tissues. More recently, it was reported that reference component analysis (RCA), an algorithm that substantially improves clustering accuracy, was developed to robustly cluster single-cell transcriptomes[]. The RCA of single-cell transcriptomes […]

RCA institution(s)
Computational and Systems Biology, Genome Institute of Singapore, Singapore; Developmental Cellomics Laboratory, Genome Institute of Singapore, Singapore; Department of Computer Science and Engineering and Center for Computational Biology, Indraprastha Institute of Information Technology, Delhi, India; Synthetic Biology, Genome Institute of Singapore, Singapore; Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore; Department of Medical Oncology, National Cancer Centre Singapore, Singapore; Department of Pathology, Singapore General Hospital, Singapore; Department of Colorectal Surgery, Singapore General Hospital, Singapore; Data Analytics Department, Institute for Infocomm Research, Singapore; Program in Cancer and Stem Cell Biology, Duke–NUS Medical School, Singapore; The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA; Department of Genetics and Genome Sciences, Institute for Systems Genomics, University of Connecticut, Farmington, CT, USA; Department of Biological Sciences, National University of Singapore, Singapore
RCA funding source(s)
Supported by the Agency for Science, Technology and Research (A*STAR), by grant JCO1331CFG080 from A*STAR’s Joint Council Office, by Agency of Science, Technology and Research grants IAF111091 and IAF111128, by industry partners Fluidigm Singapore and Becton Dickinson Holdings, and by the Strategic Positioning Fund (SPF2012/003) from the Biomedical Research Council (BMRC).

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