A class store layout information of MSA robotic loader plate.
Extends
Class "gArray", directly.
Methods
map.to.MSA
signature(x = "data.frame", y =
"MSAroboticPlate"): Return a data frame that assign samples
(represented by the input data frame) to MSA robotic plate sequentially.
map.to.MSA
signature(x = "gExperimentSetup", y =
"MSAroboticPlate"): Return a data frame that assign samples from an
gExperimentSetup object to MSA robotic plate.
show
signature(object = "MSAroboticPlate"): Shows the
layout of the plate.
Predefined objects
MSA4.plate: A predeined object of class MSAroboticPlate
that represent a 96 position plate.
BeadChip96ToMSA4MAPMap: The loading order a MSA4 robotic loader
used to load BeadChips.
See Also
gExperimentSetup
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
gSetup <- create.optimized.setup(sample=gs, container=gc, nSim=100)
out <- map.to.MSA(gSetup, MSA4.plate)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(OSAT)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/OSAT/MSAroboticPlate-class.Rd_%03d_medium.png", width=480, height=480)
> ### Name: MSAroboticPlate-class
> ### Title: Class '"MSAroboticPlate"'
> ### Aliases: MSAroboticPlate-class initialize,MSAroboticPlate-method
> ### show,MSAroboticPlate-method MSA4.plate BeadChip96ToMSA4MAP
> ### getLayout,MSAroboticPlate-method
> ### map.to.MSA,data.frame,MSAroboticPlate-method
> ### map.to.MSA,gExperimentSetup,MSAroboticPlate-method map.to.MSA
> ### Keywords: classes
>
> ### ** 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
An object of class "gSample"
The raw data are
ID SampleType Race AgeGrp
1 1 Case Hispanic (60,100]
2 2 Case Hispanic (60,100]
3 3 Case European (60,100]
4 4 Case European (50,60]
5 5 Case European (50,60]
6 6 Case European (0,30]
...
ID SampleType Race AgeGrp
571 571 Control European (40,50]
572 572 Control Hispanic (30,40]
573 573 Control European (30,40]
574 574 Control Hispanic (30,40]
575 575 Control European (40,50]
576 576 Control European (0,30]
Blocking strata in the data:
SampleType Freq sFactor
1 Case 317 1
2 Control 259 2
Optimization strata in the data
SampleType Race AgeGrp Freq oFactor
1 Case European (0,30] 8 1
2 Control European (0,30] 58 2
3 Case Hispanic (0,30] 0 3
4 Control Hispanic (0,30] 9 4
5 Case European (30,40] 21 5
6 Control European (30,40] 54 6
7 Case Hispanic (30,40] 6 7
8 Control Hispanic (30,40] 32 8
9 Case European (40,50] 34 9
10 Control European (40,50] 52 10
11 Case Hispanic (40,50] 46 11
12 Control Hispanic (40,50] 2 12
13 Case European (50,60] 40 13
14 Control European (50,60] 44 14
15 Case Hispanic (50,60] 16 15
16 Control Hispanic (50,60] 2 16
17 Case European (60,100] 84 17
18 Control European (60,100] 6 18
19 Case Hispanic (60,100] 62 19
20 Control Hispanic (60,100] 0 20
>
> gc <- setup.container(IlluminaBeadChip96Plate, 6, batch='plates')
> gc
An object of class "gContainer"
It consists of 6 IlluminaBeadChip96Plate plates.
The block level is set at plates level.
plates cFactor Freq
1 1 1 96
2 2 2 96
3 3 3 96
4 4 4 96
5 5 5 96
6 6 6 96
The container layout is
@data$container
plates chipRows chipColumns chips rows columns wells chipID rowID wellID
1 1 1 1 1 1 1 1 1 1 1
2 1 1 1 1 2 1 2 1 1 2
3 1 1 1 1 3 1 3 1 1 3
4 1 1 1 1 4 1 4 1 1 4
5 1 1 1 1 5 1 5 1 1 5
6 1 1 1 1 6 1 6 1 1 6
cFactor
1 1
2 1
3 1
4 1
5 1
6 1
...
plates chipRows chipColumns chips rows columns wells chipID rowID wellID
571 6 2 4 8 1 2 7 48 286 571
572 6 2 4 8 2 2 8 48 286 572
573 6 2 4 8 3 2 9 48 286 573
574 6 2 4 8 4 2 10 48 286 574
575 6 2 4 8 5 2 11 48 286 575
576 6 2 4 8 6 2 12 48 286 576
cFactor
571 6
572 6
573 6
574 6
575 6
576 6
>
> gSetup <- create.optimized.setup(sample=gs, container=gc, nSim=100)
Warning message:
In create.optimized.setup(sample = gs, container = gc, nSim = 100) :
Using default optimization method: optimal.shuffle
> out <- map.to.MSA(gSetup, MSA4.plate)
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.