Author: Guangchun Han; Ansam Sinjab; Warapen Treekitkarnmongkol; Patrick Brennan; Kieko Hara; Kyle Chang; Elena Bogatenkova; Beatriz Sanchez-Espiridion; Carmen Behrens; Boning Gao; Luc Girard; Jianjun Zhang; Boris Sepesi; Tina Cascone; Lauren Byers; Don L. Gibbons; Jichao Chen; Seyed Javad Moghaddam; Edwin J. Ostrin; Junya Fujimoto; Jerry Shay; John V. Heymach; John D. Minna; Steven Dubinett; Paul A. Scheet; Ignacio I. Wistuba; Edward Hill; Shannon Telesco; Christopher Stevenson; Avrum E. Spira; Linghua Wang; Humam Kadara
Title: Single-cell analysis of human lung epithelia reveals concomitant expression of the SARS-CoV-2 receptor ACE2 with multiple virus receptors and scavengers in alveolar type II cells Document date: 2020_4_17
ID: j3vruni3_18
Snippet: In addition to the bioinformatics approaches described above, all other statistical analysis was performed using R v3.6.0. Analysis of differences in genes between groups (e.g., between ACE2postive vs. ACE2-negative; smoker vs. non/light smoker) were calculated using the FindMarkers function in R. Pseudo-bulk gene expression values for defined cell clusters were calculated by taking mean expression of each gene across all cells in a specific clus.....
Document: In addition to the bioinformatics approaches described above, all other statistical analysis was performed using R v3.6.0. Analysis of differences in genes between groups (e.g., between ACE2postive vs. ACE2-negative; smoker vs. non/light smoker) were calculated using the FindMarkers function in R. Pseudo-bulk gene expression values for defined cell clusters were calculated by taking mean expression of each gene across all cells in a specific cluster. Deconvolution of AT2 cell abundance was performed on the TCGA lung adenocarcinoma cohort by incorporating AT2 signature genes defined by our study into MCP-counter, an R package that permits the quantification of the absolute abundance of immune and stromal cell populations in heterogeneous tissues from transcriptome data 20 . All statistical significance testing was two-sided, and results were considered statistically significant at p-value < 0.05. The Benjamini-Hochberg method was applied to control the . CC-BY-NC-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.04.16.045617 doi: bioRxiv preprint false discovery rate (FDR) in multiple comparisons (e.g. DEG analysis), and calculate adjusted pvalues (q-values).
Search related documents:
Co phrase search for related documents- Benjamini Hochberg method and false discovery rate: 1
- Benjamini Hochberg method and FDR false discovery rate: 1
- bioinformatic approach and describe bioinformatic approach: 1
- bioinformatic approach and discovery rate: 1
- bioinformatic approach and false discovery rate: 1
- bioinformatic approach and gene expression: 1, 2
- cell abundance and gene expression: 1, 2, 3, 4, 5, 6, 7, 8, 9
- cell cluster and gene expression: 1, 2, 3, 4, 5, 6, 7, 8
- cell population and discovery rate: 1, 2, 3
- cell population and false discovery rate: 1, 2
- cell population and gene expression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- DEG analysis and discovery rate: 1
- DEG analysis and false discovery rate: 1
- DEG analysis and FDR false discovery rate: 1
- DEG analysis and gene expression: 1, 2, 3
- discovery rate and false discovery rate: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- discovery rate and FDR false discovery rate: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25
- discovery rate and gene expression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21
- false discovery rate and gene expression: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21
Co phrase search for related documents, hyperlinks ordered by date