Selected article for: "scrna seq and Table s1"

Author: Minfeng Liao; Yang Liu; Jin Yuan; Yanling Wen; Gang Xu; Juanjuan Zhao; Lin Chen; Jinxiu Li; Xin Wang; Fuxiang Wang; Lei Liu; Shuye Zhang; Zheng Zhang
Title: The landscape of lung bronchoalveolar immune cells in COVID-19 revealed by single-cell RNA sequencing
  • Document date: 2020_2_26
  • ID: 8l1vfsbc_9
    Snippet: To characterize the immune microenvironment of the SARS-CoV-2-infected lung, we performed scRNA-seq analysis of single cells in the lung BALF (37, 820 cells) using the 10X Genomics platform, from 3 of recovered mild cases and 3 of severe cases ( Figure 1A , Table 1 ). We also collected public available scRNA-seq data (43, 627 cells) of 8 normal lungs as control [12] . This dataset passed stringent high-quality filtering ( Figure S1 ), yielding a .....
    Document: To characterize the immune microenvironment of the SARS-CoV-2-infected lung, we performed scRNA-seq analysis of single cells in the lung BALF (37, 820 cells) using the 10X Genomics platform, from 3 of recovered mild cases and 3 of severe cases ( Figure 1A , Table 1 ). We also collected public available scRNA-seq data (43, 627 cells) of 8 normal lungs as control [12] . This dataset passed stringent high-quality filtering ( Figure S1 ), yielding a mean of 188K reads/cell with median gene and unique molecular identifier (UMI) counts of 2, 070 and 6, 852, respectively (Table S1 ). Figure 1D and S2B). We were also able to detect low levels of SARS-CoV-2 transcripts in various cell populations from severe COVID-19 patients but not mild cases and controls ( Figure S2C ). We assumed that these viral transcripts were likely ambient contaminations of viral loads in the BALF.

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