Open shaln opened 2 years ago
Hello,
I have a question about the number of cells to be discarded identified using the code below.
qc.stats2 <- perCellQCFilters(per.cell, sub.fields=c("subsets_Mito_percent", "altexps_ERCC_percent")) colSums(as.matrix(qc.stats2)) ## low_lib_size low_n_features high_subsets_Mito_percent ## 0 3 128 ## high_altexps_ERCC_percent discard ## 65 189
The total number of cells to discard (189) does not match the sum of 3 + 128 + 65 = 193. Am I misunderstanding the output here?
Thank you.
Cells may be discarded for multiple reasons, e.g., a cell may be present in both the low_n_features and high_subsets_Mito_percent sets.
low_n_features
high_subsets_Mito_percent
Hello,
I have a question about the number of cells to be discarded identified using the code below.
The total number of cells to discard (189) does not match the sum of 3 + 128 + 65 = 193. Am I misunderstanding the output here?
Thank you.