Discrepancies Between matched Single-cell and Bulk Transcriptome Samples

[Rui-Jing]

Hi Tinyi,

Firstly, I would like to express my appreciation for developing BayesPrism, a user-friendly software that has significantly aided my research. However, I have encountered some issues during its application in tumor sample analysis that I hope to discuss with you:

Inconsistency in Deconvolution Results: My single-cell data is derived from tumor samples. I noticed that when I increased the number of single-cell reference samples from 4 to 8, the deconvolution results became inconsistent. This was particularly evident with some types of immune cells, such as T cells, where the results varied before and after updating the single-cell samples.

Overestimation of Microenvironment Cells: In the tumor cell deconvolution results, some microenvironment cells, such as Ependymal cells, appear to be significantly overestimated. In some samples, these cells were estimated to make up 25-35% of the population, which seems implausible.

Discrepancies Between Single-cell and Bulk Transcriptome Samples: I have samples for which both single-cell and bulk transcriptomes were analyzed. When deconvolving these samples, I found considerable differences in the cell proportions estimated from the two types of data.

Lastly, I would like to know how to effectively evaluate the accuracy and reasonableness of the deconvolution results. I look forward to your guidance and thank you in advance for your response.