bc_auto_cutoff: Finds barcode count cutoff point

In wenjie1991/CellBarocde: Cellular DNA Barcode Analysis toolkit

Description

Finds the cutoff point for the barcode count filtering based on the barcode count distribution.

Usage

bc_auto_cutoff(barcodeObj, useCleanBc = TRUE)

## S4 method for signature 'BarcodeObj'
bc_auto_cutoff(barcodeObj, useCleanBc = TRUE)

Arguments

barcodeObj	A BarcodeObj object.
useCleanBc	A logical value, if TRUE, the cleanBc slot in the BarcodeObj object will be used, otherwise the messyBc slot will be used.

Details

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.

Value

a numeric vector of the cutoff point.

Examples

data(bc_obj)

bc_auto_cutoff(bc_obj)

wenjie1991/CellBarocde documentation built on Dec. 23, 2021, 5:11 p.m.