For this week's post, I thought I’d mess around a bit with the CellXGene tool provided by the Chan Zuckerberg Institute.

It's based on a big dataset of individual cells, classified by tissue, cell type, and disease state, and their gene expression profiles (single-cell RNA counts).

You can automatically compare how gene expression looks different between sick and healthy individuals, for a variety of diseases, and drill down into which cells/tissues are different and how.

It's a fascinating toy and a great way to generate hypotheses.

Here, I’ll do it for Alzheimer's, comparing 138,438 Alzheimer's brain cells to 9,203,998 normal/healthy brain cells to see what the most “differentially expressed” genes are, and what that might tell us about how the disease works.

Top Hits

LINC01609

1.6x overexpressed in Alzheimer's, d =4.203

This is a non-protein coding RNA. Typically most expressed in the testis. In [...]

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Outline:

(01:13) Top Hits

(01:16) LINC01609

(01:21) 1.6x overexpressed in Alzheimer's, d =4.203

(01:50) SLC26A3

(01:55) 10.6x overexpressed in Alzheimer's, d = 3.310

(04:06) RASGEF1B

(04:10) 5.5x overexpressed in Alzheimer's, d=3.267

(05:17) LINGO1

(05:20) 3.9x overexpressed in Alzheimer's, d=2.799

(06:11) INO80D

(06:15) 2x overexpressed in Alzheimer's, d =2.244

(07:21) What's Going On Here?

(09:55) What Does CellxGene Get You?

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