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Cumulus provides cloud-based data analysis for large-scale single-cell and single-nucleus RNA-seq.
Li, Bo; Gould, Joshua; Yang, Yiming; Sarkizova, Siranush; Tabaka, Marcin; Ashenberg, Orr; Rosen, Yanay; Slyper, Michal; Kowalczyk, Monika S; Villani, Alexandra-Chloé; Tickle, Timothy; Hacohen, Nir; Rozenblatt-Rosen, Orit; Regev, Aviv.
Afiliação
  • Li B; Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA. bli28@mgh.harvard.edu.
  • Gould J; Division of Rheumatology, Allergy, and Immunology, Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA, USA. bli28@mgh.harvard.edu.
  • Yang Y; Department of Medicine, Harvard Medical School, Boston, MA, USA. bli28@mgh.harvard.edu.
  • Sarkizova S; Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Tabaka M; Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Ashenberg O; Division of Rheumatology, Allergy, and Immunology, Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA, USA.
  • Rosen Y; Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Slyper M; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
  • Kowalczyk MS; Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Villani AC; Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Tickle T; Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Hacohen N; Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Rozenblatt-Rosen O; Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Regev A; Division of Rheumatology, Allergy, and Immunology, Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Boston, MA, USA.
Nat Methods ; 17(8): 793-798, 2020 08.
Article em En | MEDLINE | ID: mdl-32719530
Massively parallel single-cell and single-nucleus RNA sequencing has opened the way to systematic tissue atlases in health and disease, but as the scale of data generation is growing, so is the need for computational pipelines for scaled analysis. Here we developed Cumulus-a cloud-based framework for analyzing large-scale single-cell and single-nucleus RNA sequencing datasets. Cumulus combines the power of cloud computing with improvements in algorithm and implementation to achieve high scalability, low cost, user-friendliness and integrated support for a comprehensive set of features. We benchmark Cumulus on the Human Cell Atlas Census of Immune Cells dataset of bone marrow cells and show that it substantially improves efficiency over conventional frameworks, while maintaining or improving the quality of results, enabling large-scale studies.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Análise de Sequência de RNA / Biologia Computacional / Análise de Célula Única / Sequenciamento de Nucleotídeos em Larga Escala / Computação em Nuvem Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Análise de Sequência de RNA / Biologia Computacional / Análise de Célula Única / Sequenciamento de Nucleotídeos em Larga Escala / Computação em Nuvem Idioma: En Ano de publicação: 2020 Tipo de documento: Article