An object of type 'bicreg', 'bic.glm' or 'bic.surv'
color
The color of the plot. The value "default" uses the
current default R color scheme for image. The value
"blackandwhite" produces a black and white image.
...
Other parameters to be passed to the image and axis functions.
Details
This function is a modification of the imageplot.bma
function from the BMA package. The difference is that
variables (genes) with probne0 equal to 0 are removed
before plotting. The arguments of this function is identical
to those in imageplot.bma.
Value
An heatmap-style image, with the BMA selected variables on the vertical
axis, and the BMA selected models on the horizontal axis. The variables
(genes) are sorted in descreasing order of the posterior probability
that the variable is not equal to 0 (probne0) from top to
bottom. The models are sorted in descreasing order of the
model posterior probability (postprob) from left to right.
Note
The BMA and Biobase packages are required.
References
Clyde, M. (1999)
Bayesian Model Averaging and Model Search Strategies (with discussion). In Bayesian Statistics 6. J.M. Bernardo, A.P. Dawid, J.O. Berger, and A.F.M. Smith eds. Oxford University Press, pages 157-185.
Yeung, K.Y., Bumgarner, R.E. and Raftery, A.E. (2005)
Bayesian Model Averaging: Development of an improved multi-class, gene selection and classification tool for microarray data.
Bioinformatics 21: 2394-2402.
See Also
iterateBMAglm.train
Examples
library (Biobase)
library (BMA)
library (iterativeBMA)
data(trainData)
data(trainClass)
## training phase: select relevant genes
ret.bic.glm <- iterateBMAglm.train (train.expr.set=trainData, trainClass, p=100)
## produce an image plot to visualize the selected genes and models
imageplot.iterate.bma (ret.bic.glm)
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(iterativeBMA)
Loading required package: BMA
Loading required package: survival
Loading required package: leaps
Loading required package: robustbase
Attaching package: 'robustbase'
The following object is masked from 'package:survival':
heart
Loading required package: inline
Loading required package: rrcov
Scalable Robust Estimators with High Breakdown Point (version 1.3-11)
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: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")'.
Attaching package: 'Biobase'
The following object is masked from 'package:robustbase':
rowMedians
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/iterativeBMA/imageplot_iterate_bma.Rd_%03d_medium.png", width=480, height=480)
> ### Name: imageplot.iterate.bma
> ### Title: An image plot visualization tool
> ### Aliases: imageplot.iterate.bma
> ### Keywords: classif
>
> ### ** Examples
>
> library (Biobase)
> library (BMA)
> library (iterativeBMA)
> data(trainData)
> data(trainClass)
>
> ## training phase: select relevant genes
> ret.bic.glm <- iterateBMAglm.train (train.expr.set=trainData, trainClass, p=100)
[1] "5: explored up to variable ## 100"
There were 50 or more warnings (use warnings() to see the first 50)
>
> ## produce an image plot to visualize the selected genes and models
> imageplot.iterate.bma (ret.bic.glm)
>
>
>
>
>
>
> dev.off()
null device
1
>