Question: Options for cell type deconvolution from whole blood?
1
gravatar for penny.lane
6 months ago by
penny.lane10
penny.lane10 wrote:

Hello,

My colleagues and I have human, whole blood RNA-Seq data from which we would like to estimate the proportions of various immune cell types within each sample and then see how they are changing between samples. We do not, however, have our own matched single cell RNA-Seq data set to help with the deconvolution. What methods would people recommend we consider? We're particularly interested in any methods that have already been validated to work well on whole blood samples.

Thanks!

rna-seq • 375 views
ADD COMMENTlink modified 12 days ago by E.Earley20 • written 6 months ago by penny.lane10
2
gravatar for E.Earley
12 days ago by
E.Earley20
United States
E.Earley20 wrote:

try their new CIBERSORTx

https://doi.org/10.1038/s41587-019-0114-2

https://cibersortx.stanford.edu/

Also check out SCDC

https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbz166/5699815

https://meichendong.github.io/SCDC/

ADD COMMENTlink written 12 days ago by E.Earley20

Great. Thanks for these useful information

ADD REPLYlink written 12 days ago by Shicheng Guo8.1k
1
gravatar for trausch
6 months ago by
trausch1.4k
Germany
trausch1.4k wrote:

Cibersort could be an option.

ADD COMMENTlink written 6 months ago by trausch1.4k

Yeah, this is one that caught my attention, but according to their website the LM22 signature was designed & validated on microarray data and they warn against applying it to RNA-Seq data. They say they are in the process of deriving and validating a signature for RNA-Seq data, but no release dates are given. Any other ideas?

ADD REPLYlink written 6 months ago by penny.lane10

I think array data will be more stable. rna-seq data should have high depth to receive same level accuracy.

ADD REPLYlink written 5 months ago by Shicheng Guo8.1k
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