R: Function to compute the raw and scaled Gene expression Grade...
ggi
R Documentation
Function to compute the raw and scaled Gene expression Grade Index (GGI)
Description
This function computes signature scores and risk classifications from gene expression values following the algorithm used for the Gene expression Grade Index (GGI).
Matrix of gene expressions with samples in rows and probes in columns, dimnames being properly defined.
annot
Matrix of annotations with at least one column named "EntrezGene.ID", dimnames being properly defined.
do.mapping
TRUE if the mapping through Entrez Gene ids must be performed (in case of ambiguities, the most variant probe is kept for each gene), FALSE otherwise.
mapping
Matrix with columns "EntrezGene.ID" and "probe" used to force the mapping such that the probes are not selected based on their variance.
hg
Vector containing the histological grade (HG) status of breast cancer patients in the dataset.
verbose
TRUE to print informative messages, FALSE otherwise.
Value
score
Continuous signature scores
risk
Binary risk classification, 1 being high risk and 0 being low risk.
mapping
Mapping used if necessary.
probe
If mapping is performed, this matrix contains the correspondence between the gene list (aka signature) and gene expression data.
Author(s)
Benjamin Haibe-Kains
References
Sotiriou C, Wirapati P, Loi S, Harris A, Bergh J, Smeds J, Farmer P, Praz V, Haibe-Kains B, Lallemand F, Buyse M, Piccart MJ and Delorenzi M (2006) "Gene expression profiling in breast cancer: Understanding the molecular basis of histologic grade to improve prognosis", Journal of National Cancer Institute, 98:262–272
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)
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Type 'license()' or 'licence()' for distribution details.
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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(genefu)
Loading required package: survcomp
Loading required package: survival
Loading required package: prodlim
Loading required package: mclust
Package 'mclust' version 5.2
Type 'citation("mclust")' for citing this R package in publications.
Loading required package: limma
Loading required package: biomaRt
Loading required package: iC10
Loading required package: pamr
Loading required package: cluster
Loading required package: iC10TrainingData
Loading required package: AIMS
Loading required package: e1071
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 object is masked from 'package:limma':
plotMA
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
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'citation("Biobase")', and for packages 'citation("pkgname")'.
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/genefu/ggi.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ggi
> ### Title: Function to compute the raw and scaled Gene expression Grade
> ### Index (GGI)
> ### Aliases: ggi
> ### Keywords: prognosis
>
> ### ** Examples
>
> ## load GGI signature
> data(sig.ggi)
> ## load NKI dataset
> data(nkis)
> ## compute relapse score
> ggi.nkis <- ggi(data=data.nkis, annot=annot.nkis, do.mapping=TRUE,
+ hg=demo.nkis[ ,"grade"])
> table(ggi.nkis$risk)
0 1
71 79
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> dev.off()
null device
1
>