Selected article for: "cell subset and positive cell"

Author: Christoph Muus; Malte D Luecken; Gokcen Eraslan; Avinash Waghray; Graham Heimberg; Lisa Sikkema; Yoshihiko Kobayashi; Eeshit Dhaval Vaishnav; Ayshwarya Subramanian; Christopher Smillie; Karthik Jagadeesh; Elizabeth Thu Duong; Evgenij Fiskin; Elena Torlai Triglia; Christophe Becavin; Meshal Ansari; Peiwen Cai; Brian Lin; Justin Buchanan; Sijia Chen; Jian Shu; Adam L Haber; Hattie Chung; Daniel T Montoro; Taylor Adams; Hananeh Aliee; Samuel J Allon; Zaneta Andrusivova; Ilias Angelidis; Orr Ashenberg; Kevin Bassler; Christophe Becavin; Inbal Benhar; Joseph Bergenstrahle; Ludvig Bergenstrahle; Liam Bolt; Emelie Braun; Linh T Bui; Mark Chaffin; Evgeny Chichelnitskiy; Joshua Chiou; Thomas M Conlon; Michael S Cuoco; Marie Deprez; David S Fischer; Astrid Gillich; Joshua Gould; Minzhe Guo; Austin J Gutierrez; Arun C Habermann; Tyler Harvey; Peng He; Xiaomeng Hou; Lijuan Hu; Alok Jaiswal; Peiyong Jiang; Theodoros Kapellos; Christin S Kuo; Ludvig Larsson; Michael A Leney-Greene; Kyungtae Lim; Monika Litvinukova; Ji Lu; Leif S Ludwig; Wendy Luo; Henrike Maatz; Elo Maddissoon; Lira Mamanova; Kasidet Manakongtreecheep; Charles-Hugo Marquette; Ian Mbano; Alexi M McAdams; Ross J Metzger; Ahmad N Nabhan; Sarah K Nyquist; Jose Ordovas-Montanes; Lolita Penland; Olivier B Poirion; Segio Poli; CanCan Qi; Daniel Reichart; Ivan Rosas; Jonas Schupp; Rahul Sinha; Rene V Sit; Kamil Slowikowski; Michal Slyper; Neal Smith; Alex Sountoulidis; Maximilian Strunz; Dawei Sun; Carlos Talavera-Lopez; Peng Tan; Jessica Tantivit; Kyle J Travaglini; Nathan R Tucker; Katherine Vernon; Marc H Wadsworth; Julia Waldman; Xiuting Wang; Wenjun Yan; Ali Onder Yildirim; William Zhao; Carly G K Ziegler; Aviv Regev
Title: Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells
  • Document date: 2020_4_20
  • ID: nkql7h9x_27
    Snippet: To explore such gene programs in a broader context, we identified signatures for dual-positive ACE2 + TMPRSS2 + cells compared to dual-negative ACE2 -TMPRSS2cells in the nasal epithelium, lung, and gut (Supplementary Tables 6, 7 8) with two complementary approaches. The first aimed to find features that characterize programs of dual positive cells that are shared by different cell types in one tissue ("tissue programs"). The second aimed to find .....
    Document: To explore such gene programs in a broader context, we identified signatures for dual-positive ACE2 + TMPRSS2 + cells compared to dual-negative ACE2 -TMPRSS2cells in the nasal epithelium, lung, and gut (Supplementary Tables 6, 7 8) with two complementary approaches. The first aimed to find features that characterize programs of dual positive cells that are shared by different cell types in one tissue ("tissue programs"). The second aimed to find features that are associated with dual positive cells compared to other cells of the same type, and may or may not be shared with other types ("cell programs") (Methods). To infer tissue programs, we trained a random forest classifier to discriminate between dual-positive and dual-negative cells (excluding ACE2 and TMPRSS2; 75:25 class balanced test-train split), generalizing across multiple cell types in one tissue, and ranked genes according to their importance scores in the classifier (Methods). To infer cell programs, we performed differential expression analysis between dual-positive and dualnegative cells within each cell subset. We note that ACE2 + TMPRSS2 + cells have more unique transcripts detected (Extended Data Fig. 10b) : this can reflect a technical confounder, biological features, or both. We conservatively controlled for these differences (by sampling dual positive and dual negative cells from matched gene complexity bins; Methods; Extended Data Fig. 10b , Extended Data Fig. 11) . Importantly, these methods do not assume that ACE2 + TMPRSS2 + cells form a distinct subset within each cell type. Rather, our goal is to leverage the variation among single cells within a single type to identify gene programs that are co-regulated with ACE2 and TMPRSS2 within each expressing cell subset.

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