Brain cell type deconvolution

Question

[rodd]

Hi all!

I am interested in understanding the % of main cell types composing my bulk RNA-seq data from brain (e.g., astrocytes, microglia, neurons, oligodendrocytes). However, from what I gathered, this appears to be an extremely complicated task. I came across CiberSortX, but I couldn't find a good tutorial for it. There are no accessible instructions about what the input files should look like, how to treat the RNA-seq data, etc. And even the idea of selecting and processing the appropriate dataset (single-cell RNA-seq, or RNA-seq performed on sorted cells) seems a bit daunting.

Has any of you conducted this type of analysis for bulk RNA-seq tissue from brain? Do you know any tutorial or tool that could help me achieve this more easily, or it's not gonna be that easy either way?

Thank you!

[Aspire]

Maybe you can try this : https://voineagulab.shinyapps.io/BrainDeconvShiny/

Article at https://www.nature.com/articles/s41467-022-28655-4

Answer 1

[jv]

There are several detailed tutorials available for CiberSortX, but you have to register for the software in order to access them.

For additional info on prepping your bulk RNA-seq data you can also review the Methods section of the CibserSortX paper https://doi.org/10.1038/s41587-019-0114-2.

Answer 2

[LChart]

The PsychEncode consortium performed cell type deconvolution using non-negative least squares (https://www.science.org/doi/10.1126/science.aat8464) and they provide the cell-by-gene expression targets as a resource (http://resource.psychencode.org/). DeconRNAseq implements this for you; though it underperforms its weighted version (MuSiC) which performs competitively with CiberSort (source: https://www.nature.com/articles/s41467-022-28655-4). Check the supplementary material of this paper for their approach to running these alternative (open-source) deconvolution methods.