bioRxiv preprint doi: https://doi.org/10.1101/2020.07.06.182634; this version posted July 6, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Gene Expression Network Analysis Provides Potential Targets Against SARS-CoV-2 2 Ana I. Hernández Cordero1*, Xuan Li1, Chen Xi Yang1, Stephen Milne1,2,3, Yohan Bossé4, Philippe 3 Joubert4, Wim Timens5, Maarten van den Berge6, David Nickle7, Ke Hao8, Don D. Sin1,2 4 5 1 Centre for Heart Lung Innovation, University of British Columbia, Vancouver, BC, Canada 6 2 Division of Respiratory Medicine, Faculty of Medicine, University of British Columbia, Vancouver, 7 BC, Canada 8 3 Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia 9 4 Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval, Québec City, 10 QC, Canada 11 5 University of Groningen, University Medical Centre Groningen, Department of Pathology and 12 Medical Biology, Groningen, The Netherlands 13 6 University of Groningen, University Medical Center Groningen, Department of Pulmonary Diseases, 14 Groningen, The Netherlands 15 7 Merck Research Laboratories, Genetics and Pharmacogenomics, Boston, Massachusetts, United 16 States of America 17 8 Department of Genetics and Genomic Sciences and Icahn Institute for Data Science and Genomic 18 Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America 19 20 * Corresponding author 21 E-mail:
[email protected] 22 23 24 25 26 27 28 29 30 31 32 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.07.06.182634; this version posted July 6, 2020.