Danko-Lab
Question about calculate the immune cell fraction in bulk sequencing of tumor sample
Dear developers:
First of all, thank you for developing this great algorithms, it really helped my research. I try to find the specific immune cell fraction in a bulk dataset containing multiple cancer. But in this project, the reference scRNA dataset just contain 3 cancer type, which means only 3 types of cancer cell can be included as the reference for buliding the Prism object. But the bulk dataset containing 10 cancers. So i wonder can i just use the non-tumor cells as the reference in buliding the Prism object and what problem may this method cause in using BayesPrism if i do not include the tumor cell.
Thanks for your help!
Dear user,
Thank you for your interest in our methods.
It is always recommended to use the most comprehensive representation of cell types to build the scRNA-seq reference, as the statistical model assumes that all cell types are found in the reference and their fractions sum to one.
If only using non-tumor cells, the BayesPrism will distribute reads from tumor cell to the cell type that are most similar to tumor cell in the reference, and hence inflate its fraction.
I was not quite sure what is exactly meant when you say 3 cancer type. Typically, it is recommended to deconvolve one cancer type, e.g. GBM or lung cancer, at a time, using the scRNA-seq from the matched cancer type to build the reference.
Best,
Tinyi
On Mon, Aug 12, 2024 at 5:11 AM threshold233 @.***> wrote:
Dear developers:
First of all, thank you for developing this great algorithms, it really helped my research. I try to find the specific immune cell fraction in a bulk dataset containing multiple cancer. But in this project, the reference scRNA dataset just contain 3 cancer type, which means only 3 types of cancer cell can be included as the reference for buliding the Prism object. But the bulk dataset containing 10 cancers. So i wonder can i just use the non-tumor cells as the reference in buliding the Prism object and what problem may this method cause in using BayesPrism if i do not include the tumor cell.
Thanks for your help!
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