ggi: Function to compute the raw and scaled Gene expression Grade...

In genefu: Computation of Gene Expression-Based Signatures in Breast Cancer

Description

This function computes signature scores and risk classifications from gene expression values following the algorithm used for the Gene expression Grade Index (GGI).

Usage

ggi(data, annot, do.mapping = FALSE, mapping, hg, verbose = FALSE)

Arguments

data	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

See Also

gene76

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)

Example output

Loading required package: survcomp
Loading required package: survival
Loading required package: prodlim
Loading required package: mclust
Package 'mclust' version 5.4.2
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, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colMeans, colSums, 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, rowMeans, rowSums, rownames, sapply,
    setdiff, sort, table, tapply, union, unique, unsplit, which,
    which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


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genefu documentation built on Jan. 28, 2021, 2:01 a.m.