I am using 1000 cells from a normal brain snRNAseq experiment https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE168408 to use as a reference for calling tumour in my CNS data.
When I run pipelineCNA() the output datable has the 1000 cells up top as 'confidentNormal' but some of these cells are being called tumour by the pipeline:
In the end ~50 cells are being classified as tumour despite being healthy tissue, and also being specifically provided as a normal ref:
> scevan.df <- scevan.df[which(scevan.df$confidentNormal=="yes"), ]
> table(scevan.df$class)
filtered normal tumor
60 889 51
When looking at the initial heatmap, it looks like there probably aren't any tumour cells in the sample:
Is that what is throwing it off? I would still expect everything to be called as normal, rather than have the reference also labelled as tumour.
The cells being labelled as tumour are likely immune cells in the brain since they're all cell cycle quiet and CD45 high:
I am using 1000 cells from a normal brain snRNAseq experiment https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE168408 to use as a reference for calling tumour in my CNS data.
When I run pipelineCNA() the output datable has the 1000 cells up top as 'confidentNormal' but some of these cells are being called tumour by the pipeline:
In the end ~50 cells are being classified as tumour despite being healthy tissue, and also being specifically provided as a normal ref:
When looking at the initial heatmap, it looks like there probably aren't any tumour cells in the sample:
Is that what is throwing it off? I would still expect everything to be called as normal, rather than have the reference also labelled as tumour.
The cells being labelled as tumour are likely immune cells in the brain since they're all cell cycle quiet and CD45 high: