bc_auto_cutoff {CellBarcode} | R Documentation |
Finds the cutoff point for the barcode count filtering based on the barcode count distribution.
bc_auto_cutoff(barcodeObj, useCleanBc = TRUE) ## S4 method for signature 'BarcodeObj' bc_auto_cutoff(barcodeObj, useCleanBc = TRUE)
barcodeObj |
A |
useCleanBc |
A logical value, if |
The one dimension kmeans clustering is applied for identify the "true barcode" based on read count. The the algorithm detail is: 1. Remove the barcodes with count below the median of counts. 2. Transform the count by log2(x+1). 3. Apply the 1 dimension clustering to the logarized count, with the cluster number of 2 and weights of the logarized count. 4. Choose the minimum count value in the cluster with higher count as cutoff point.
For more info about 1 dimension kmeans used here please refer to
Ckmeans.1d.dp
, which has been used here.
a numeric vector
of the cutoff point.
data(bc_obj) bc_auto_cutoff(bc_obj)