Editorial: Methods for Single-Cell and Microbiome Sequencing Data

Front Genet. 2022 May 13:13:920191. doi: 10.3389/fgene.2022.920191. eCollection 2022.

Himel Mallick¹, Lingling An^{2

3

4}, Mengjie Chen⁵, Pei Wang^{6

7}, Ni Zhao⁸

¹ Biostatistics and Research Decision Sciences, Merck & Co.Inc., Rahway, NJ, United States.
² Interdisciplinary Program in Statistics and Data Science, The University of Arizona, Tucson, AZ, United States.
³ Department of Epidemiology and Biostatistics, The University of Arizona, Tucson, AZ, United States.
⁴ Department of Biosystems Engineering, The University of Arizona, Tucson, AZ, United States.
⁵ Department of Human Genetics and Department of Medicine, University of Chicago, Chicago, IL, United States.
⁶ Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
⁷ Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
⁸ Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, United States.

No abstract available

Keywords: biostatistics; computational biology; data science; microbiome; multi-omics; omics; single-cell; statistics.

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