Comments (1)
for the 10x, I think you might refer to the wrong reference. We had two batch of 10x data. The first batch have around 900 cells (3 cell lines), second have around 4000 cells(5 cell lines). For sc_CEL-seq2 5 cell line mixtures (3X384 well plate), there are more doublets than we would expect so we exclude this data when we compare some methods, such as clustering. The Drop-seq data contains around 200 cells.
The gene count matrixs were acquired by scPipe, which contains top X cells ranked by reads and it does not perform QC in preprocessing step. So the cell number in gene count matrix does not reflact the real cell number, just result of the parameter.
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Related Issues (15)
- All the methods tested in the paper all limited in R language? HOT 1
- How to perform log transformation? HOT 3
- some question about clustering HOT 5
- Question regarding 10x UMIs HOT 1
- Is the 10X data 3' or 5'? Which chemistry was used? HOT 1
- can't reproduce the results in the paper HOT 1
- Plans to make into ExperimentHub package? HOT 3
- five cancer cell line 10x data barcode+UMI length
- mitochondrial RNA
- A query about theoretical total input of spike-ins HOT 2
- known cell grouping variable HOT 2
- Fix encoding(?) of the *_call.R scripts in script/clustering/Clustering_Algorithms HOT 1
- Rdata file contains variables with unclear names HOT 1
- Loading the data from Python HOT 2
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