pam50: PAM50 classifier for identification of breast cancer...

Description Usage Format Details Source References Examples

Description

List of parameters defining the PAM50 classifier for identification of breast cancer molecular subtypes (Parker et al 2009).

Usage

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Format

List of parameters for PAM50:

centroids

Gene expression centroids for each subtype.

centroids.map

Mapping for centroids.

method.cor

Method of correlation used to compute distance to the centroids.

method.centroids

Method used to compute the centroids.

std

Method of standardization for gene expressions ("none", "scale" or "robust").

mins

Minimum number of samples within each cluster allowed during the fitting of the model.

Details

Three versions of the model are provided, each of ones differs by the gene expressions standardization method since it has an important impact on the subtype classification:

pam50

Use of the official centroids without scaling of the gene expressions.

pam50.scale

Use of the official centroids with traditional scaling of the gene expressions (see scale).

pam50.robust

Use of the official centroids with robust scaling of the gene expressions (see rescale).

The model pam50.robust has been shown to reach the best concordance with the traditional clinical parameters (ER IHC, HER2 IHC/FISH and histological grade). However the use of this model is recommended only when the dataset is representative of a global population of breast cancer patients (no sampling bias, the 5 subtypes should be present).

Source

http://jco.ascopubs.org/cgi/content/short/JCO.2008.18.1370v1

References

Parker, Joel S. and Mullins, Michael and Cheang, Maggie C.U. and Leung, Samuel and Voduc, David and Vickery, Tammi and Davies, Sherri and Fauron, Christiane and He, Xiaping and Hu, Zhiyuan and Quackenbush, John F. and Stijleman, Inge J. and Palazzo, Juan and Marron, J.S. and Nobel, Andrew B. and Mardis, Elaine and Nielsen, Torsten O. and Ellis, Matthew J. and Perou, Charles M. and Bernard, Philip S. (2009) "Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes", Journal of Clinical Oncology, 27(8):1160–1167

Examples

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Example output

Loading required package: survcomp
Loading required package: survival
Loading required package: prodlim
Loading required package: mclust
Package 'mclust' version 5.3
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")'.

List of 7
 $ method.cor      : chr "spearman"
 $ method.centroids: chr "mean"
 $ std             : chr "none"
 $ rescale.q       : num 0.05
 $ mins            : num 5
 $ centroids       : num [1:50, 1:5] 0.718 0.537 -0.575 -0.119 0.3 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:50] "ACTR3B" "ANLN" "BAG1" "BCL2" ...
  .. ..$ : chr [1:5] "Basal" "Her2" "LumA" "LumB" ...
 $ centroids.map   :'data.frame':	50 obs. of  3 variables:
  ..$ probe          : chr [1:50] "ACTR3B" "ANLN" "BAG1" "BCL2" ...
  ..$ probe.centroids: chr [1:50] "ACTR3B" "ANLN" "BAG1" "BCL2" ...
  ..$ EntrezGene.ID  : int [1:50] 57180 54443 573 596 332 644 891 898 991 990 ...
List of 7
 $ method.cor      : chr "spearman"
 $ method.centroids: chr "mean"
 $ std             : chr "robust"
 $ rescale.q       : num 0.05
 $ mins            : num 5
 $ centroids       : num [1:50, 1:5] 0.718 0.537 -0.575 -0.119 0.3 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:50] "ACTR3B" "ANLN" "BAG1" "BCL2" ...
  .. ..$ : chr [1:5] "Basal" "Her2" "LumA" "LumB" ...
 $ centroids.map   :'data.frame':	50 obs. of  3 variables:
  ..$ probe          : chr [1:50] "ACTR3B" "ANLN" "BAG1" "BCL2" ...
  ..$ probe.centroids: chr [1:50] "ACTR3B" "ANLN" "BAG1" "BCL2" ...
  ..$ EntrezGene.ID  : int [1:50] 57180 54443 573 596 332 644 891 898 991 990 ...
Warning message:
system call failed: Cannot allocate memory 

genefu documentation built on May 2, 2018, 2:10 a.m.