Plot GenesRanking

Description

Plots the posterior probability of the genes ordered by class ranking.

Usage

## S3 method for class 'GenesRanking'
plot(x, y="missing", numGenesPlot=1000, 
    plotTitle="Significant genes", lpThreshold = 0.95, ...)

Arguments

Details

Significant genes: Genes with posterior probability over 'lpThreshold'.
More significant genes may mean:

• Very different class

• More systemic disease

Plot lines represet the posterior probability of genes, sorted by rank from left to right.

In order to find genes that diferentiate the classes from each other, the function ranks the genes bassed on their posterior probability for each class.
The posterior probability represents how well a gene differentiates samples from a class, from samples from other classes. Therefore, Genes with high posterior probability are good to differentiate a class from all the others.
This posterior probability is calculated by emfit (pkg:EBarrays), an expectation-maximization (EM) algorithm for gene expression mixture model.

Value

Posterior probability plot of the top genes.

Examples

# Load or calculate a ranking (or a classifier with geNetClassifier)
data(leukemiasClassifier) # Sample trained classifier, @genesRanking

# Default plot:
plot(leukemiasClassifier@genesRanking)

# Changing options:
plot(leukemiasClassifier@genesRanking, 
    numGenesPlot=5000, plotTitle="Leukemias", lpThreshold=0.9)

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(geNetClassifier)
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")'.

Loading required package: EBarrays
Loading required package: lattice
Loading required package: minet
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/geNetClassifier/plot.GenesRanking.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot.GenesRanking
> ### Title: Plot GenesRanking
> ### Aliases: plotGenesRanking plot.GenesRanking plot,GenesRanking-method
> ### Keywords: classif
> 
> ### ** Examples
> 
> # Load or calculate a ranking (or a classifier with geNetClassifier)
> data(leukemiasClassifier) # Sample trained classifier, @genesRanking
> 
> # Default plot:
> plot(leukemiasClassifier@genesRanking)
> 
> # Changing options:
> plot(leukemiasClassifier@genesRanking, 
+     numGenesPlot=5000, plotTitle="Leukemias", lpThreshold=0.9)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>