Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity

Welch JD, Kozareva V, Ferreira A, Vanderburg C, Martin C, Macosko EZ. Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity. Cell. 2019 Jun 13; 177(7):1873-1887.e17. PMID.

GEO: GSE126836

Defining cell types requires integrating diverse single-cell measurements from multiple experiments and biological contexts. To flexibly model single-cell datasets, we developed LIGER, an algorithm that delineates shared and dataset-specific features of cell identity. We applied it to four diverse and challenging analyses of human and mouse brain cells. First, we defined region-specific and sexually dimorphic gene expression in the mouse bed nucleus of the stria terminalis. Second, we analyzed expression in the human substantia nigra, comparing cell states in specific donors and relating cell types to those in the mouse. Third, we integrated in situ and single-cell expression data to spatially locate fine subtypes of cells present in the mouse frontal cortex. Finally, we jointly defined mouse cortical cell types using single-cell RNA-seq and DNA methylation profiles, revealing putative mechanisms of cell-type-specific epigenomic regulation. Integrative analyses using LIGER promise to accelerate investigations of cell-type definition, gene regulation, and disease states.

This study features raw and processed data used in our analyses of the human SN and mouse BNST. Stay tuned for clustering/visualization data!

If you're interested in trying out LIGER for your own analyses, check out the code on Github!

Data download: Raw (BAMs and FASTQs) and processed data are available under the Download tab (you must sign in to SCP before you can access the data). BNST data were generated with 10xChromium Single Cell 3' v3, while SN data were generated with 10xChromium Single Cell 3' v2. Unfortunately, we cannot host raw human data on SCP; to access SN BAMs, please use our GEO accession number above. Raw BNST data is organized by individual (7 female mouse BNST, 8 male mouse BNST). Processed SN data is organized by individual, and has been filtered for cells with >= 1200 UMIs, with putative doublets removed. Processed BNST data is organized by sex, and is included at two different filtration levels. BNST_only files correspond to neurons localized specifically to the BNST, while BNST-region-neur files correspond to neurons localized to the wider BNST region. (Note that barcode and gene csv files corresponding to expression matrices are listed under Other Data.) We have also included two liger objects containing 74910 BNST only neurons and 40453 SN neurons respectively, with original clustering and factorization calculations.