Class "flowTransResult"

Description

Class that contains the results of a call to flowTrans on a flowFrame

Objects from the Class

Objects can be created by calls of the form new("flowTransResult", ...). The object contains three slots: the transformed flowFrame, a transform object from which the parameters can be extracted, and a dims slot containing a character vector of the dimensions that have been transformed.

Slots

result:

Object of class "flowFrame". The transformed data.

trans:

Object of class "transform". The transform applied to the flowFrame. Parameters can be extracted via summary(trans).

dims:

Object of class "character". The names of the dimensions that have been transformed.

Methods

summary

signature(object = "flowTransResult"): Summarize the transformed data.

Author(s)

Greg Finak <greg.finak@ircm.qc.ca>, Raphael Gottardo <raphael.gottardo@ircm.qc.ca>.

References

Finak G, Perez JM, Weng A, Gottardo R. Optimizing Data Transformation for Flow Cytometry.

See Also

extractParams summary

Examples

m <- t(matrix(rnorm(10000),2))
colnames(m) <- c("A","B")
m <- flowFrame(m)
res <- flowTrans(m,"mclMultivBoxCox", c("A","B"),
                 n2f=FALSE, parameters.only=FALSE)
summary(res)
extractParams(res)

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(flowTrans)
Loading required package: flowCore
Loading required package: flowViz
Loading required package: lattice
Loading required package: flowClust
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:flowCore':

    normalize, sort

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: graph
Loading required package: RBGL
Loading required package: ellipse
Loading required package: mnormt
Loading required package: corpcor
Loading required package: clue

Attaching package: 'flowClust'

The following object is masked from 'package:graphics':

    box

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/flowTrans/flowTransResult-class.Rd_%03d_medium.png", width=480, height=480)
> ### Name: flowTransResult-class
> ### Title: Class "flowTransResult"
> ### Aliases: flowTransResult-class flowTransResult
> ###   summary,flowTransResult-class
> ### Keywords: classes
> 
> ### ** Examples
> 
> m <- t(matrix(rnorm(10000),2))
> colnames(m) <- c("A","B")
> m <- flowFrame(m)
> res <- flowTrans(m,"mclMultivBoxCox", c("A","B"),
+                  n2f=FALSE, parameters.only=FALSE)
> summary(res)
Transformation: 
[1] "mclMultivBoxCox"
Transformed Results: 
flowFrame object 'anonymous'
with 5000 cells and 2 observables:
  name desc    range  minRange maxRange
A    A    A 2.468640 -4.729593 2.468640
B    B    B 3.206168 -4.477737 3.206168
0 keywords are stored in the 'description' slot

Transformation parameters:
    theta 
0.9826028 
> extractParams(res)
$A
    theta 
0.9826028 

$B
    theta 
0.9826028 

> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>