dot-getChannelCentres: Find the centres of each of the wells in a given channel.

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

Description

The plate should have been classified by k-means clustering.

Usage

.getChannelCentres(plate, cMethod, channel, minSeparation = 2000)

Arguments

plate	A ddpcrPlate object from which to extract the centres.
cMethod	The classification method to use (in the form of a character string).
channel	An integer 1 or 2 corresponding to the channel of interest.
minSeparation	The minimum distance required between two cluster centres in order for us to assume that k-means found two distinct clusters. Defaults to 2000.

Value

A list of data frames, where each data frame has information about the centres in the channel of interest.

Author(s)

Anthony Chiu, [e-mail]

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