simcells: simcells

In CONFESS: Cell OrderiNg by FluorEScence Signal

Description

The main function to simulate spots of various numbers, sizes, signals in one or multiple images of a given dimension.

Usage

simcells(channels = 2, spots.per.image = c(1, 1),
  one.location = c(50, 50), image.dimension = rep(100, 2),
  signal.level = list(700, 700), noise.level = c(200, 200),
  spot.size = list(30, 30), agreement.number = 1)

Arguments

channels	Integer. The number of channels for each sample. Default is 2.
spots.per.image	Numeric vector. The number of spots in each image (channel). The length of the vector equals to the number of channels. Default is one spot per channel.
one.location	Numeric vector. The central location of the matched spots across the channels (in pixel) coordinates. Default is (X,Y) = (50,50).
image.dimension	Numeric vector. The image dimension (in pixels). Default is 100 x 100.
signal.level	List. The lambda parameter of the Poisson distribution that generates the true spot (pixel) signals. The list has as many components (length) as the number of channels. The number of elements of each component equals to the number of spots in each particular channel. Default is list(700,700).
noise.level	Numeric vector. The sigma parameter of the Normal distribution that generates the image noise level. The length of the vector equals to the number of channels. Default is c(200,200).
spot.size	List. The size of each spot on each channel (in pixels). The list has as many components (length) as the number of channels. The number of elements of each component equals to the number of spots in each particular channel. Default is list(30,30).
agreement.number	Integer. It defines how many spot pairs are matched, i.e. they are located in the same coordinates across channels. These reflect true cells. Default is 1 corresponding to a single-cell case study.

Value

The image(s) with the generated spot(s). It consists of the data matrices and the location of the spot centers.

Examples

r<-simcells(channels = 2, spots.per.image = c(2, 3), one.location = c(50, 50),
image.dimension = rep(200, 2), signal.level = list(c(1000, 1000), c(1000, 700, 300)),
noise.level = c(100, 100),spot.size = list(c(81, 100), c(26, 29, 50)), agreement.number = 1)

r<-simcells(channels = 2, spots.per.image = c(0, 0), image.dimension = rep(200, 2),
signal.level = list(c(),c()),noise.level = c(0, 0), spot.size = list(c(), c()))

CONFESS documentation built on Nov. 8, 2020, 6:05 p.m.