getCutOff: Find the standard deviation of droplets (in a given class)...

In CRUKMI-ComputationalBiology/twoddpcr: Classify 2-d Droplet Digital PCR (ddPCR) data and quantify the number of starting molecules

Description

For a specified class, take a data frame of droplet amplitudes and compute the standard deviation multiplied by a level of accuracy.

Usage

getCutOff(droplets, cl, level = 3, classCol = "class")

Arguments

droplets	A data frame of droplets with "Ch1.Amplitude" and "Ch2.Amplitude" columns, as well as a class column (see classCol).
cl	The class to focus on. Typically one of "NN", "PN", "NP" and "PP".
level	A constant by which we will multiply the standard deviation. Defaults to 5.
classCol	The column (name or number) from 'droplets' representing the class.

Value

A list with named elements 'ch1' and 'ch2', each giving the error bound for the corresponding channel. If the number of droplets is either 0 or 1, return list(ch1=0, ch2=0) to avoid any errors. Otherwise, return level * (sd of the droplets in each channel).

Author(s)

Anthony Chiu, [e-mail]

CRUKMI-ComputationalBiology/twoddpcr documentation built on Feb. 14, 2021, 9:18 p.m.