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Interactive analysis and quality assessment of single-cell copy-number variations

By Tyler Garvin, Robert Aboukhalil, Jude Kendall, Timour Baslan, Gurinder S. Atwal, James Hicks, Michael Wigler, Michael C Schatz

Posted 12 Nov 2014
bioRxiv DOI: 10.1101/011346 (published DOI: 10.1038/nmeth.3578)

We present an open-source visual-analytics web platform, Ginkgo (http://qb.cshl.edu/ginkgo), for the interactive analysis and quality assessment of single-cell copy-number alterations. Ginkgo automatically constructs copy-number profiles of individual cells from mapped reads, as well as constructing phylogenetic trees of related cells. We validate Ginkgo by reproducing the results of five major studies and examine the data characteristics of three commonly used single-cell amplification techniques to conclude DOP-PCR to be the most consistent for CNV analysis.

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