bc_auto_cutoff.RdFinds the cutoff point for the barcode count filtering based on the barcode count distribution.
bc_auto_cutoff(barcodeObj, useCleanBc = TRUE)
# S4 method for BarcodeObj
bc_auto_cutoff(barcodeObj, useCleanBc = TRUE)A BarcodeObj object.
A logical value, if TRUE, the cleanBc slot
in the BarcodeObj object will be used, otherwise the messyBc
slot will be used.
a numeric vector of the cutoff point.
The one dimension kmeans clustering is applied to identify the "true barcode" based on the read count. The algorithm detail is: 1. Remove the barcodes with counts below the median of counts. 2. Transform the count by log2(x+1). 3. Apply the 1-dimension clustering to the log count, with the cluster number of 2 and weights of the log count. 4. Choose the minimum count value in the cluster with more counts as cutoff point.
For more info about 1 dimension kmeans used here please refer to
Ckmeans.1d.dp.
data(bc_obj)
bc_auto_cutoff(bc_obj)
#> ------------
#> bc_auto_cutoff: cleanBc is used.
#> ------------
#> test1 test2
#> 104 53