Hi all,
I've got some bulk RNA-seq data (mouse brain/hippocampus) and I'm looking for tools to extract celltype composition proportions from the data. I've been looking around and most of the tools focus on using associated single-cell data, which I do not have.
Do you know of any tool which provides celltype predictions (mouse brain) by only inputting bulk RNA-seq (e.g. using internal cell reference datasets)?
If not, is the best strategy to get some public single-cell data to use with my bulk RNA-seq (from what I've read, via MuSiC or CIBERSORTx for example)? In that case, could you recommend (if there exist) databases providing single-cell data with annotated celltypes (instead of raw, unannotated data) which I could use?
If not, what would be the best strategy to achieve this goal?
thanks for your help
2 answers
Do you know of any tool which provides celltype predictions (mouse brain) by only inputting bulk RNA-seq (e.g. using internal cell reference datasets)?
As soon as you search for tools published before 2019, the majority of deconvolution methods will probably be based on bulk RNA-seq alone. See, for example, this review from 2018.
If not, is the best strategy to get some public single-cell data to use with my bulk RNA-seq (from what I've read, via MuSiC or CIBERSORTx for example)?
Dorshizi et al, 2021 demonstrate the use of reference scRNA-seq data sets for brain-specific questions.
In that case, could you recommend (if there exist) databases providing single-cell data with annotated celltypes (instead of raw, unannotated data) which I could use?
- The Allen Brain Atlas is an incredible resource for transcriptomic (scRNA-seq) data from Mouse and Human data sets. I usually find a tad bit easier to first identify the paper with the corresponding data that I might be interested in and then track down the data on the Allen Brain Atlas servers, but I'm sure you can pick your way through.
- The scRNAseq package from bioconductor has a range of scRNA-seq data sets ready to load including cell labels
- the [SingleCell Portal[(https://singlecell.broadinstitute.org/single_cell) may be of help, too.
Apart from that, identifying publications with data sets of interest, e.g. via Pubmed or via GEO, should lead you to promising scRNAseq data set candidates; most of them should be provided with metadata (e.g. cell labels).
Here's another good resource for scRNA-seq atlas data. There is brain data in there along with annotated cell types. https://descartes.brotmanbaty.org/
Hello,
I would like to do a similar thing, deconvolution of bulk rna-seq data from mouse brain cortex. The disease I am focusing is neurodegenerative. Can I ask what package/software you finally used for your analysis? Because so far I found that some popular tools e.g., Cybersort, xCell are primarily for tumor and immune cells.
I have read the article Dorshizi et al., 2021 recommended by Friederike, but if I am understanding correctly, the cellR package in the article is for human data rather than mouse.
Many thanks!
Log in to answer this question.
-
Change of cell proportions or differential expression?
written by Aspire
-
Creating a Single-Cell Signature Matrix for Bulk RNA-seq Deconvolution
written by Lloyd98 •
-
Infering the cell composition from bulk RNA-seq data for mouse
written by feather-W •
-
scRNA-seq cell type mapping neuron VS glia proportion
written by Song •
-
Brain cell type deconvolution
written by rodd
-
Simulating single cell and bulk RNA-seq data accounting for gene-gene correlations
written by ali_karimnezhad •
-
Single-cell RNA Seq on whole organ or whole tissue with known cell origins
written by zhang.jianhai •
-
Is it wrong to deconvolute bulk RNA seq data of a tissue using scRNAseq data of a different tissue?
written by tushard1987 •
-
Data integration tools for multi-omics sequencing data
written by marina.v.yurieva
-
How to assess extent of cell-type admixtures from bulk RNA-seq data for a single tissue?
written by nancy
