LitCovid-sentences  

PMC:7252096 / 114990-117749 JSONTXT 10 Projects

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Id Subject Object Predicate Lexical cue
T823 0-39 Sentence denotes Nasal Washes during Influenza Infection
T824 40-123 Sentence denotes Sample processing, sequencing, and analysis was performed as in (Cao et al., 2020).
T825 124-206 Sentence denotes Reads were aligned to the GRCh37 reference genome combined with influenza genomes.
T826 207-392 Sentence denotes Mapped reads from each sample were then corrected for Drop-seq barcode synthesis error using the Drop-seq core computational tools developed by the McCarroll Lab (Macosko et al., 2015).
T827 393-554 Sentence denotes Genes were quantified using End Sequence Analysis Toolkit (ESAT, github/garber-lab/ESAT) with parameters -wlen 100 -wOlap 50 -wExt 0 -scPrep (Derr et al., 2016).
T828 555-752 Sentence denotes Finally, UMIs that likely result from sequencing errors were corrected by merging any UMIs that were observed only once and have 1 hamming distance from a UMI detected by two or more aligned reads.
T829 753-812 Sentence denotes Only cell barcodes with more than 1,000 UMIs were analyzed.
T830 813-881 Sentence denotes Cell barcodes with mostly erythrocyte genes (HBA, HBB) were removed.
T831 882-968 Sentence denotes From here on, the remaining cell barcodes in the matrix would be referred to as cells.
T832 969-1063 Sentence denotes The final gene by cell matrix was normalized using the scran package v3.10 (Lun et al., 2016).
T833 1064-1259 Sentence denotes The normalized matrix was used for dimensionality reduction by first selecting variable genes that had a high coefficient of variance (CV) and were expressed (> = 1 UMI) by more than three cells.
T834 1260-1488 Sentence denotes Influenza viral genes, interferon stimulated genes, and cell cycle related genes were removed from the variable gene list in order to minimize the impact of viral responses and mitosis on clustering and cell type identification.
T835 1489-1699 Sentence denotes This resulted in the selection of 2484 variable genes. t-distributed stochastic neighbor embedding (tSNE) was applied to the first ten principal components (PCs), which explained 95% of the total data variance.
T836 1700-1888 Sentence denotes Density clustering (Rodriguez and Laio, 2014) was performed on the resulting tSNE coordinates and identified four major clusters: epithelial cells, neutrophils, macrophages and leukocytes.
T837 1889-2049 Sentence denotes The epithelial cell cluster and the leukocyte cluster were then re-clustered independently, as described above, to identify populations within each metacluster.
T838 2050-2244 Sentence denotes Specifically, the epithelial cell cluster was re-embedded using 2629 variable genes selected by the same criteria mentioned in the previous section and 13 PCs that explained 95% of the variance.
T839 2245-2318 Sentence denotes Density clustering over the epithelial cell subset revealed ten clusters.
T840 2319-2449 Sentence denotes Differential gene expression analysis using edgeR (Robinson et al., 2010) was performed to identify marker genes for each cluster.
T841 2450-2759 Sentence denotes Influenza-infected and bystander cells were identified after correcting for sample-specific distribution of ambient influenza mRNA contamination and predicted cells most likely to be infected identified using a hurdle zero inflated negative binomial (ZINB) model and a support vector machine (SVM) classifier.