bc_auto_cutoff | 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 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
.
a numeric vector
of the cutoff point.
data(bc_obj)
bc_auto_cutoff(bc_obj)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.