gExperimentSetup-class: Class '"gExperimentSetup"'

In llrs/OSAT: OSAT: Optimal Sample Assignment Tool

Description

A class stores all relevant informations related to the experimantal sample assgnment.

Details

Function create.experiment.setup() create a block randomized experiment assignment, without optimization step.

Functions optimal.shuffle() and optimal.block optimize setup using different optimization methods.

Functiion create.optimized.setup() create a optimized setup directly.

Slots

expSetup:

Object of class "data.frame". A data frame represents the sample placement to well locations in the container.

data:

Object of class "list". A list that hold a gSample object, a gContainer object and assignment link the two objects.

summaryInfo:

Object of class "list". Some summary of the sample, container and assignment.

metadata:

Object of class "list". Metadata of the object.

Accessors

get.gAssembly

signature(x = "gExperimentSetup"): Get the chip/plate assembly used for container.

samples

signature(x = "gExperimentSetup"): Return the gSample object.

get.gContainer

: ...

metadata

signature(x = "gExperimentSetup"): Get the metadata.

metadata<-

signature(x = "gExperimentSetup"): Set the metadata.

Related Methods

map.to.MSA

signature(x = "gExperimentSetup", y = "MSAroboticPlate"): A method map the experiment setup to a set of MSA 96 wells robotic plates.

plot

signature(x = "gExperimentSetup", y = "missing"): Visual

show

signature(object = "gExperimentSetup"): ...

summary

signature(object = "gExperimentSetup"): ...

get.experiment.setup

: Return a data frame with linked sample and container information.

See Also

MSAroboticPlate

Examples

library("OSAT")
# data as an example
inPath <- system.file("extdata", package="OSAT")
pheno <- read.table(file.path(inPath, 'samples.txt'), header=TRUE, sep="\t")

## create object to hold sample information
gs <- setup.sample(pheno,  optimal=c("SampleType", "Race", "AgeGrp"), strata=c("SampleType") )
gs

gc <- setup.container(IlluminaBeadChip96Plate, 6, batch='plates')
gc

gSetup0 <- create.experiment.setup(sample=gs, container=gc)

llrs/OSAT documentation built on May 23, 2019, 7:18 a.m.