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Last data update: 2014.03.03

R: Jackknife between group analysis

bga.jackknife

R Documentation

Jackknife between group analysis

Description

Performs one-leave-out jackknife analysis of a between group analysis as described by Culhane et al., 20002

Usage

bga.jackknife(data, classvec, ...)

Arguments

`data`	Input dataset. A `matrix`, `data.frame` If the input is gene expression data in a `matrix` or `data.frame`. The columns contain the cases (array samples) which will be jackknifed.
`classvec`	A factor or vector which describes the classes in the training dataset
`...`	further arguments passed to or from other methods

Details

Performs a one-leave-out cross validation of between group analysis bga. Input is a training dataset. This can take 5-10 minutes to compute on standard data gene expression matrix.

In jackknife one leave out analysis, one case (column) is removed. The remaining dataset is subjected to bga. Then the class of the case that was removed is predicted using suppl. This analysis is repeated until all samples have been removed and predicted.

Value

A list containing

`results`	The projected co-ordinates of each sample
`summary`	A summary of number and percentage of correctly assigned samples

Author(s)

Aedin Culhane

References

Culhane et al., 2002 Between-group analysis of microarray data. Bioinformatics. 18(12):1600-8.

Examples

data(khan)
# NOTE using a very reduced dataset (first 5 genes) to speed up results
# hence expect poor prediction accuracy
dim(khan$train)
print("using only small subset of data")
if (require(ade4, quiet = TRUE)) {
bga.jackknife(khan$train[1:5,], khan$train.classes) }

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(made4)
Loading required package: ade4
Loading required package: RColorBrewer
Loading required package: gplots

Attaching package: 'gplots'

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

    lowess

Loading required package: scatterplot3d
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/made4/bga.jackknife.Rd_%03d_medium.png", width=480, height=480)
> ### Name: bga.jackknife
> ### Title: Jackknife between group analysis
> ### Aliases: bga.jackknife
> ### Keywords: manip multivariate
> 
> ### ** Examples
> 
> data(khan)
> # NOTE using a very reduced dataset (first 5 genes) to speed up results
> # hence expect poor prediction accuracy
> dim(khan$train)
[1] 306  64
> print("using only small subset of data")
[1] "using only small subset of data"
> if (require(ade4, quiet = TRUE)) {
+ bga.jackknife(khan$train[1:5,], khan$train.classes) }
$results
        projected.Axis1 projected.Axis2 projected.Axis3 closest.centre
EWS.T1  "0.1796938"     "0.03223652"    "-0.007871632"  "BL-NHL"      
EWS.T2  "-0.125328"     "-0.319135"     "-0.2287313"    "BL-NHL"      
EWS.T3  "0.01650144"    "-0.2214479"    "-0.03602944"   "EWS"         
EWS.T4  "0.2935052"     "-0.4814553"    "0.2344584"     "EWS"         
EWS.T6  "0.006695328"   "-0.1210627"    "0.08177354"    "BL-NHL"      
EWS.T7  "-0.1347209"    "-0.1625475"    "0.0938616"     "EWS"         
EWS.T9  "-0.1180192"    "0.1788036"     "-0.1873782"    "BL-NHL"      
EWS.T11 "-0.1195324"    "-0.1757967"    "-0.09588219"   "BL-NHL"      
EWS.T12 "0.1697188"     "-0.05806945"   "0.1671593"     "BL-NHL"      
EWS.T13 "0.05373105"    "-0.6032833"    "-0.6315504"    "EWS"         
EWS.T14 "0.08813719"    "-0.2153136"    "0.09667327"    "EWS"         
EWS.T15 "0.146521"      "0.04995045"    "-0.1953851"    "NB"          
EWS.T19 "-0.04370983"   "-0.315936"     "-0.07859392"   "EWS"         
EWS.C8  "-0.04759317"   "-0.2372032"    "0.3754341"     "BL-NHL"      
EWS.C3  "-0.01094925"   "-0.5422011"    "0.1952465"     "NB"          
EWS.C2  "-0.1101239"    "-0.5219158"    "0.402939"      "BL-NHL"      
EWS.C4  "0.1252794"     "-0.1825572"    "0.3817637"     "BL-NHL"      
EWS.C6  "0.0248968"     "-0.2263948"    "0.2265657"     "BL-NHL"      
EWS.C9  "0.0207777"     "0.2286145"     "-0.246718"     "BL-NHL"      
EWS.C7  "-0.1222711"    "-0.4859269"    "0.1965064"     "BL-NHL"      
EWS.C1  "-0.07323107"   "-0.6550264"    "0.3634392"     "BL-NHL"      
EWS.C11 "0.1996836"     "0.1170902"     "-0.08535846"   "BL-NHL"      
EWS.C10 "-0.04709414"   "-0.4456142"    "0.2857149"     "BL-NHL"      
BL.C5   "-0.3360787"    "0.3983337"     "-0.1581871"    "EWS"         
BL.C6   "-0.2633225"    "-0.157719"     "-0.1879632"    "EWS"         
BL.C7   "-0.2883659"    "0.2950372"     "0.005083449"   "EWS"         
BL.C8   "-0.3138421"    "-0.2549557"    "0.2324113"     "EWS"         
BL.C1   "-0.2978599"    "0.02127647"    "-0.1861221"    "EWS"         
BL.C2   "0.2838852"     "-0.2359142"    "-0.3283124"    "EWS"         
BL.C3   "-0.3192533"    "-0.3114449"    "0.1163196"     "EWS"         
BL.C4   "-0.1984428"    "-0.08848847"   "-0.255106"     "NB"          
NB.C1   "-0.07212391"   "0.4230518"     "0.1042882"     "NB"          
NB.C2   "-0.2567298"    "0.2357264"     "0.4167948"     "BL-NHL"      
NB.C3   "0.08101795"    "0.3793929"     "-0.018477"     "NB"          
NB.C6   "0.1689642"     "0.1048352"     "-0.8762314"    "NB"          
NB.C12  "-0.08278157"   "0.3260882"     "-0.2646231"    "BL-NHL"      
NB.C7   "-0.2419152"    "0.5501103"     "0.3514848"     "EWS"         
NB.C4   "0.05515949"    "0.2372994"     "-0.2090818"    "BL-NHL"      
NB.C5   "0.1359181"     "0.2843813"     "0.5645355"     "NB"          
NB.C10  "0.1000748"     "0.3690235"     "0.2335781"     "NB"          
NB.C11  "0.2211195"     "0.1625705"     "-0.6989649"    "NB"          
NB.C9   "0.09287289"    "0.3175016"     "0.208423"      "NB"          
NB.C8   "0.07025343"    "0.246857"      "0.6906177"     "NB"          
RMS.C4  "-0.1112484"    "0.2594798"     "0.1772258"     "EWS"         
RMS.C3  "0.0859698"     "0.2083831"     "-0.01015805"   "BL-NHL"      
RMS.C9  "0.02546633"    "0.3453482"     "-0.0834719"    "BL-NHL"      
RMS.C2  "0.03651873"    "0.04518854"    "0.450465"      "NB"          
RMS.C5  "-0.3106005"    "0.1482998"     "-0.001127675"  "RMS"         
RMS.C6  "-0.4309918"    "0.02587858"    "0.04920602"    "RMS"         
RMS.C7  "-0.1013133"    "-0.3613495"    "0.355274"      "BL-NHL"      
RMS.C8  "-1.00568"      "0.2170205"     "-0.2338543"    "RMS"         
RMS.C10 "0.1433004"     "0.552715"      "-0.05142717"   "NB"          
RMS.C11 "-1.286855"     "-0.1830049"    "0.008736643"   "RMS"         
RMS.T1  "-1.039903"     "-0.3569595"    "-0.05238069"   "RMS"         
RMS.T4  "-1.254748"     "-0.3043582"    "-0.01637328"   "RMS"         
RMS.T2  "-0.7605771"    "-0.2943144"    "0.2629191"     "RMS"         
RMS.T6  "-0.4168394"    "-0.1562053"    "-0.3047386"    "RMS"         
RMS.T7  "-1.028674"     "-0.5278885"    "0.3033742"     "RMS"         
RMS.T8  "1.70252"       "-0.4094267"    "-0.2917236"    "RMS"         
RMS.T5  "-0.4234762"    "-0.06268887"   "0.08741641"    "RMS"         
RMS.T9  "-0.1365803"    "-0.4133518"    "-0.7096112"    "EWS"         
RMS.T3  "0.1138166"     "-0.4632831"    "-0.2457821"    "EWS"         
RMS.T10 "-1.190226"     "-0.1443788"    "-0.01427886"   "RMS"         
RMS.T11 "-0.5447798"    "0.143907"      "0.1980633"     "RMS"         
        predicted true.class
EWS.T1  "RMS"     "EWS"     
EWS.T2  "BL-NHL"  "EWS"     
EWS.T3  "EWS"     "EWS"     
EWS.T4  "EWS"     "EWS"     
EWS.T6  "BL-NHL"  "EWS"     
EWS.T7  "NB"      "EWS"     
EWS.T9  "BL-NHL"  "EWS"     
EWS.T11 "BL-NHL"  "EWS"     
EWS.T12 "BL-NHL"  "EWS"     
EWS.T13 "EWS"     "EWS"     
EWS.T14 "NB"      "EWS"     
EWS.T15 "NB"      "EWS"     
EWS.T19 "EWS"     "EWS"     
EWS.C8  "BL-NHL"  "EWS"     
EWS.C3  "RMS"     "EWS"     
EWS.C2  "BL-NHL"  "EWS"     
EWS.C4  "BL-NHL"  "EWS"     
EWS.C6  "BL-NHL"  "EWS"     
EWS.C9  "BL-NHL"  "EWS"     
EWS.C7  "BL-NHL"  "EWS"     
EWS.C1  "BL-NHL"  "EWS"     
EWS.C11 "BL-NHL"  "EWS"     
EWS.C10 "BL-NHL"  "EWS"     
BL.C5   "EWS"     "BL-NHL"  
BL.C6   "EWS"     "BL-NHL"  
BL.C7   "EWS"     "BL-NHL"  
BL.C8   "EWS"     "BL-NHL"  
BL.C1   "EWS"     "BL-NHL"  
BL.C2   "EWS"     "BL-NHL"  
BL.C3   "EWS"     "BL-NHL"  
BL.C4   "NB"      "BL-NHL"  
NB.C1   "NB"      "NB"      
NB.C2   "RMS"     "NB"      
NB.C3   "NB"      "NB"      
NB.C6   "NB"      "NB"      
NB.C12  "BL-NHL"  "NB"      
NB.C7   "BL-NHL"  "NB"      
NB.C4   "BL-NHL"  "NB"      
NB.C5   "NB"      "NB"      
NB.C10  "NB"      "NB"      
NB.C11  "NB"      "NB"      
NB.C9   "NB"      "NB"      
NB.C8   "NB"      "NB"      
RMS.C4  "BL-NHL"  "RMS"     
RMS.C3  "RMS"     "RMS"     
RMS.C9  "BL-NHL"  "RMS"     
RMS.C2  "NB"      "RMS"     
RMS.C5  "RMS"     "RMS"     
RMS.C6  "RMS"     "RMS"     
RMS.C7  "BL-NHL"  "RMS"     
RMS.C8  "BL-NHL"  "RMS"     
RMS.C10 "BL-NHL"  "RMS"     
RMS.C11 "RMS"     "RMS"     
RMS.T1  "RMS"     "RMS"     
RMS.T4  "RMS"     "RMS"     
RMS.T2  "RMS"     "RMS"     
RMS.T6  "EWS"     "RMS"     
RMS.T7  "EWS"     "RMS"     
RMS.T8  "RMS"     "RMS"     
RMS.T5  "RMS"     "RMS"     
RMS.T9  "NB"      "RMS"     
RMS.T3  "RMS"     "RMS"     
RMS.T10 "EWS"     "RMS"     
RMS.T11 "BL-NHL"  "RMS"     

$summary
  No.correct No.incorrect     %correct 
       22.00        42.00        34.38 

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