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HBA scRNAseq

The Human Brain Atlas (HBA)1 is a single-cell RNA sequencing (scRNAseq) dataset. The HBA dataset was derived from 106 dissections of the brains of 3 post-mortem donors. The result is gene expression profiles from over 3 million brain cells.

Clustering

HBA analysts applied hierarchical clustering algorithms to the gene expression levels of these ~3 million cells to create clusters at 3 scales: subclusters, clusters, and superclusters. Accordingly, brain cell types in the HBA dataset are defined in an unbiased, data-driven way.

In the figure below from Silleti et al,1, the left panel illustrates the dissected regions of the brain, while the right panel shows a t-SNE plot of brain cells, with each cell colored according to its supercluster. hba-plot

Utility

The HBA dataset can be combined with MAGMA2 to associate GWAS phenotypes with HBA-defined brain cell types.

  1. Kimberly Siletti, Rebecca Hodge, Alejandro Mossi Albiach, Ka Wai Lee, Song-Lin Ding, Lijuan Hu, Peter Lönnerberg, Trygve Bakken, Tamara Casper, Michael Clark, and others. Transcriptomic diversity of cell types across the adult human brain. Science, 382(6667):eadd7046, 2023. URL: https://www.science.org/doi/abs/10.1126/science.add7046. ↩↩

  2. Christiaan A De Leeuw, Joris M Mooij, Tom Heskes, and Danielle Posthuma. MAGMA: generalized gene-set analysis of GWAS data. PLoS Computational Biology, 11(4):e1004219, 2015. URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004219. ↩