genius: Function to compute the Gene Expression progNostic Index...
In genefu: Computation of Gene Expression-Based Signatures in Breast Cancer

Description Usage Arguments Value Author(s) References See Also Examples

This function computes the Gene Expression progNostic Index Using Subtypes (GENIUS) as published by Haibe-Kains et al. 2010. Subtype-specific risk scores are computed for each subtype signature separately and an overall risk score is computed by combining these scores with the posterior probability to belong to each of the breast cancer molecular subtypes.

1	genius(data, annot, do.mapping = FALSE, mapping, do.scale = TRUE)

`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.
`do.scale`	`TRUE` if the ESR1, ERBB2 and AURKA (module) scores must be rescaled (see `rescale`), `FALSE` otherwise.

`GENIUSM1`	Risk score from the ER-/HER2- subtype signature in GENIUS model.
`GENIUSM2`	Risk score from the HER2+ subtype signature in GENIUS model.
`GENIUSM3`	Risk score from the ER+/HER2- subtype signature in GENIUS model.
`score`	Overall risk prediction as computed by the GENIUS model.

Benjamin Haibe-Kains

Haibe-Kains B, Desmedt C, Rothe F, Sotiriou C and Bontempi G (2010) "A fuzzy gene expression-based computational approach improves breast cancer prognostication", Genome Biology, 11(2):R18

subtype.cluster.predict,sig.score

## load NKI dataset
data(nkis)
## compute GENIUS risk scores based on GENIUS model fitted on VDX dataset
genius.nkis <- genius(data=data.nkis, annot=annot.nkis, do.mapping=TRUE)
str(genius.nkis)
## the performance of GENIUS overall risk score predictions are not optimal
## since only part of the NKI dataset was used

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

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List of 4
 $ GENIUSM1: atomic [1:150] 0.791 -0.148 -0.205 0.386 0.465 ...
  ..- attr(*, "q1")= Named num -0.101
  .. ..- attr(*, "names")= chr "2.5%"
  ..- attr(*, "q2")= Named num 0.0953
  .. ..- attr(*, "names")= chr "97.5%"
 $ GENIUSM2: atomic [1:150] 0.493 -0.762 0.515 0.434 0.358 ...
  ..- attr(*, "q1")= Named num -0.414
  .. ..- attr(*, "names")= chr "2.5%"
  ..- attr(*, "q2")= Named num 0.227
  .. ..- attr(*, "names")= chr "97.5%"
 $ GENIUSM3: atomic [1:150] -0.586 0.884 -0.178 -0.937 -0.927 ...
  ..- attr(*, "q1")= Named num -0.148
  .. ..- attr(*, "names")= chr "2.5%"
  ..- attr(*, "q2")= Named num 0.188
  .. ..- attr(*, "names")= chr "97.5%"
 $ score   : Named num [1:150] -0.586 0.884 -0.178 -0.936 -0.925 ...
  ..- attr(*, "names")= chr [1:150] "NKI_123" "NKI_327" "NKI_291" "NKI_370" ...