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      SCOPIT: sample size calculations for single-cell sequencing experiments

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          Abstract

          Background

          In single cell DNA and RNA sequencing experiments, the number of cells to sequence must be decided before running an experiment, and afterwards, it is necessary to decide whether sufficient cells were sampled. These questions can be addressed by calculating the probability of sampling at least a defined number of cells from each subpopulation (cell type or cancer clone).

          Results

          We developed an interactive web application called SCOPIT (Single-Cell One-sided Probability Interactive Tool), which calculates the required probabilities using a multinomial distribution ( www.navinlab.com/SCOPIT). In addition, we created an R package called pmultinom for scripting these calculations.

          Conclusions

          Our tool for fast multinomial calculations provide a simple and intuitive procedure for prospectively planning single-cell experiments or retrospectively evaluating if sufficient numbers of cells have been sequenced. The web application can be accessed at navinlab.com/SCOPIT.

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          Most cited references4

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          Punctuated Copy Number Evolution and Clonal Stasis in Triple-Negative Breast Cancer

          Aneuploidy is a hallmark of breast cancer; however, our knowledge of how these complex genomic rearrangements evolve during tumorigenesis is limited. In this study we developed a highly multiplexed single-nucleus-sequencing method to investigate copy number evolution in triple-negative breast cancer patients. We sequenced 1000 single cells from 12 patients and identified 1–3 major clonal subpopulations in each tumor that shared a common evolutionary lineage. We also identified a minor subpopulation of non-clonal cells that were classified as: 1) metastable, 2) pseudo-diploid, or 3) chromazemic. Phylogenetic analysis and mathematical modeling suggest that these data are unlikely to be explained by the gradual accumulation of copy number events over time. In contrast, our data challenge the paradigm of gradual evolution, showing that the majority of copy number aberrations are acquired at the earliest stages of tumor evolution, in short punctuated bursts, followed by stable clonal expansions that form the tumor mass.
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            A Representation for Multinomial Cumulative Distribution Functions

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              Estimating species richness

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                Author and article information

                Contributors
                nnavin@mdanderson.org
                Journal
                BMC Bioinformatics
                BMC Bioinformatics
                BMC Bioinformatics
                BioMed Central (London )
                1471-2105
                12 November 2019
                12 November 2019
                2019
                : 20
                : 566
                Affiliations
                [1 ]ISNI 0000 0001 2291 4776, GRID grid.240145.6, Department of Genetics, , The University of Texas MD Anderson Cancer Center, ; Houston, TX USA
                [2 ]ISNI 0000 0001 2291 4776, GRID grid.240145.6, The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, ; Houston, TX USA
                [3 ]ISNI 0000 0001 2291 4776, GRID grid.240145.6, Department of Bioinformatics and Computational Biology, , The University of Texas MD Anderson Cancer Center, ; Houston, TX USA
                Article
                3167
                10.1186/s12859-019-3167-9
                6852764
                31718533
                950d664b-49dd-4e0e-8ac3-67820afc3242
                © The Author(s). 2019

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 20 February 2019
                : 21 October 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000048, American Cancer Society;
                Award ID: 129098-RSG-16-092-01-TBG
                Funded by: CPRIT
                Award ID: RP180684
                Funded by: Susan G. Komen ()
                Award ID: PDF17487910
                Award Recipient :
                Funded by: American Association for Cancer Research ()
                Award ID: 174042GAO
                Award Recipient :
                Funded by: U.S. National Library of Medicine ()
                Award ID: 4T15LM007093-25
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: R01CA240526
                Funded by: Chan-Zuckerberg Initiative
                Award ID: MCA3-0000000147
                Categories
                Software
                Custom metadata
                © The Author(s) 2019

                Bioinformatics & Computational biology
                single cell sequencing,sample size,multinomial distributions

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