TiedemannLab
commented
3 years ago Hi Pentayouth
The quality of the sciCNV result will reflect the quality of the data and controls that you employ. To avoid CNV noise due to gene expression differences between lineages, the control cells should resemble the test population as closely as possible with respect to lineage and scRNA-seq coverage, but should of course be diploid cells.
Baseline adjustment is possible in sciCNV and in our application is used to enhance the detection of copy number gain or loss in test cell populations whose average DNA content diverges substantially from diploid - for each example the baseline can be adjusted in the positive range for cell populations with multiple trisomies, or negatively for cells with multiple monosomies and less that a diploid complement of DNA.
I hope this helps with your efforts,
kind regards, Rodger
From: Pentayouth @.> Sent: Wednesday, April 7, 2021 12:13 AM To: TiedemannLab/sciCNV @.> Cc: Subscribed @.***> Subject: [External] [TiedemannLab/sciCNV] Questions about control cell selection and multiple baseline (#2)
Dear sciCNV developers,
I have 2 questions about sciCNV regarding control cell selection and multiple baseline feature.
Firstly, I would like to ask if gene expression data from control cells of a DIFFERENT lineage is acceptable for developing expression disparity scores? I believe it is a more common situation in solid tumor single cell experiment, where malignant epithelial cells and normal NON-epithelial cells (like immune cells and stroma cells) are mixing up together and normal epithelial cells are usually absent. It would be helpful if immune cells and stroma cells could function as control cells.
Secondly, since inferCNV allows multiple baseline for different cell types, does sciCNV also support this feature?
Best regards, Pentayouth
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Pentayouth
23ycjiang
Dear sciCNV developers,
I have 2 questions about sciCNV regarding control cell selection and multiple baseline feature.
Firstly, I would like to ask if gene expression data from control cells of a DIFFERENT lineage is acceptable for developing expression disparity scores? I believe it is a more common situation in solid tumor single cell experiment, where malignant epithelial cells and normal NON-epithelial cells (like immune cells and stroma cells) are mixing up together and normal epithelial cells are usually absent. It would be helpful if immune cells and stroma cells could function as control cells.
Secondly, since inferCNV allows multiple baseline for different cell types, does sciCNV also support this feature?
Best regards, Pentayouth