Single-cell RNA-sequencing of CD14+ monocyte differentiation with M-CSF stimulus

We obtained single-cell RNA-sequencing (scRNA-seq) profiles of CD14+ monocytes isolated from human peripheral blood at 0, 3 and 6 days after M-CSF stimulation (to differentiate the cells into macrophages) across multiple donors. Integration of single-cell RNA sequencing (scRNA-seq) data from multiple experiments, laboratories, and technologies can uncover biological insights, but current methods for scRNA-seq data integration are limited by a requirement for datasets to derive from functionally similar cells. We use a novel algorithm, Scanorama, to identify and merge the shared cell types among all pairs of datasets and to accurately integrate heterogeneous scRNA-seq datasets. Scanorama is sensitive to subtle temporal changes within the same cell lineage, successfully integrating functionally similar cells across time series data of CD14+ monocytes at different stages of differentiation into macrophages. Scanorama is not only able to differentiate between completely disparate cell types but is also sensitive to subtler transcriptional changes within a cell type due to processes like stimulation. Overall design: scRNA-seq of human CD14+ monocytes at 0, 3, and 6 days after M-CSF stimulation in multiple donors

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Hie B, Bryson B, Berger B