Scientists discover key 'culprits' in major lungcancer study NatureComms
function was then used to calculate per-cell expression levels for fibroblast and mural cell gene signatures and fibroblasts were identified as those cells where the fibroblast signature score - mural cell signature score >0.1 and the fibroblast signature score >0.
A consensus list of fibroblast genes was then identified as those expressed in >1% of fibroblasts in each dataset. The Seurat packagefunction was then used to calculate rPCA corrected expression values for these consensus fibroblast genes within each dataset.The fibroblasts isolated from each scRNA-seq datasets were integrated using canonical correlation analysis dimensionality reduction to create a shared low-dimensional space across datasets.
To infer differentiation trajectories, we used the destiny R package to perform diffusion map dimensionality reduction, cluster cells by diffusion pseudotime branches and calculate pseudotime values. A loess regression model was then used to identify genes that were differentially expressed in and calculate fitted values for each gene’s expression profile in pseudotime for each dataset, using the gam R package.
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