R: Function to compute the 70 genes prognosis profile (GENE70)...
gene70
R Documentation
Function to compute the 70 genes prognosis profile (GENE70) as published by van't Veer et al. 2002
Description
This function computes signature scores and risk classifications from gene expression values following the algorithm used for the 70 genes prognosis profile (GENE70) as published by van't Veer et al. 2002.
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.
std
Standardization of gene expressions: scale for traditional standardization based on mean and standard deviation, robust for standardization based on the 0.025 and 0.975 quantiles, none to keep gene expressions unchanged.
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
L. J. van't Veer and H. Dai and M. J. van de Vijver and Y. D. He and A. A. Hart and M. Mao and H. L. Peterse and K. van der Kooy and M. J. Marton and A. T. Witteveen and G. J. Schreiber and R. M. Kerkhiven and C. Roberts and P. S. Linsley and R. Bernards and S. H. Friend (2002) "Gene Expression Profiling Predicts Clinical Outcome of Breast Cancer", Nature, 415:530–536.
See Also
nkis
Examples
## load GENE70 signature
data(sig.gene70)
## load NKI dataset
data(nkis)
## compute relapse score
rs.nkis <- gene70(data=data.nkis)
table(rs.nkis$risk)
## note that the discrepancies compared to the original publication
## are closed to the official cutoff, raising doubts on its exact value.
## computation of the signature scores on a different microarray platform
## load VDX dataset
data(vdxs)
## compute relapse score
rs.vdxs <- gene70(data=data.vdxs, annot=annot.vdxs, do.mapping=TRUE)
table(rs.vdxs$risk)
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)
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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
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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
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/genefu/gene70.Rd_%03d_medium.png", width=480, height=480)
> ### Name: gene70
> ### Title: Function to compute the 70 genes prognosis profile (GENE70) as
> ### published by van't Veer et al. 2002
> ### Aliases: gene70
> ### Keywords: prognosis
>
> ### ** Examples
>
> ## load GENE70 signature
> data(sig.gene70)
> ## load NKI dataset
> data(nkis)
> ## compute relapse score
> rs.nkis <- gene70(data=data.nkis)
> table(rs.nkis$risk)
0 1
66 84
> ## note that the discrepancies compared to the original publication
> ## are closed to the official cutoff, raising doubts on its exact value.
> ## computation of the signature scores on a different microarray platform
> ## load VDX dataset
> data(vdxs)
> ## compute relapse score
> rs.vdxs <- gene70(data=data.vdxs, annot=annot.vdxs, do.mapping=TRUE)
> table(rs.vdxs$risk)
0 1
100 50
>
>
>
>
>
> dev.off()
null device
1
>