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Maximizing statistical power to detect clinically associated cell states with scPOST
View ORCID ProfileNghia Millard, View ORCID ProfileIlya Korsunsky, Kathryn Weinand, Chamith Y. Fonseka, Aparna Nathan, Joyce B. Kang, View ORCID ProfileSoumya Raychaudhuri
doi: https://doi.org/10.1101/2020.11.23.390682
Nghia Millard
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
2Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
3Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
4Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
5Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
Ilya Korsunsky
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
2Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
3Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
4Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
5Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
Kathryn Weinand
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
2Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
3Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
4Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
5Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
Chamith Y. Fonseka
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
2Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
3Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
4Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
5Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
Aparna Nathan
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
2Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
3Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
4Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
5Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
Joyce B. Kang
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
2Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
3Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
4Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
5Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
Soumya Raychaudhuri
1Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA
2Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
3Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
4Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
5Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
6Versus Arthritis Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
Article usage
Posted November 23, 2020.
Maximizing statistical power to detect clinically associated cell states with scPOST
Nghia Millard, Ilya Korsunsky, Kathryn Weinand, Chamith Y. Fonseka, Aparna Nathan, Joyce B. Kang, Soumya Raychaudhuri
bioRxiv 2020.11.23.390682; doi: https://doi.org/10.1101/2020.11.23.390682
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