Integration of single-cell RNA-sequencing data across tissues and cancer types towards immune cell characterization

<p>To better understand dendritic cell states and subtypes, we collected individual single-cell RNAseq datasets from various studies and further integrated, batch corrected, and reprocessed the data using Besca (https://github.com/bedapub/besca).</p> <p>The following files are included:<br> 1) study_table_integrated_DCs.xlsx -&nbsp;contains a list of studies from where the datasets were gathered.<br> 2)&nbsp; int_dcs.raw.h5ad - An anndata object file containing the combined raw single-cell counts for DCs from individual studies. The datasets were joined based on the union of variables.<br> 3) intersection_genes_integrated_dcs.tsv - List of genes if the datasets were joined based on the intersection of variables. These variables were used in the subsequent analyses.</p> <p>4) int_dcs.annotated.h5ad - An anndata object file containing single-cell logarithmized counts for DCs data&nbsp;that have been integrated and reprocessed. The rows of the file contain cells, and the columns contain highly variable genes. A sparse matrix containing the logarithmized counts from all the genes (from the intersection genes integrated dcs.tsv file) can also be found (adata.raw.X) in the object. In the observations, cell-type annotation is available at three different hierarchal levels.<br> <br> This data was further&nbsp;used to produce results&nbsp;for the publication (https://jitc.bmj.com/content/10/6/e004268) on the effects of Toll-like receptor 8 agonists on conventional DCs.</p>