PAM50Classify: 'classify' subjects with PAM50 molecular signature

In pbcmc: Permutation-Based Confidence for Molecular Classification

Description

Obtain PAM50 subtype using genefu centroid Spearman's correlation implementation. If std=="median" probes with the same mapping are averaged. Then, the complete database is center normalized using gene median expression. This is done in order to assure selecting the same "gene" to those in "genefu" library, instead of the most variant probe (default in geneid.map), when more than one probe match the same gene. This selection is based on probe population variance that could depends on the number of accounted genes.

Usage

## S4 method for signature 'PAM50'
classify(object, std = c("none", "scale", "robust",   
    "median")[1], verbose = getOption("verbose", default = FALSE))  

Arguments

object	a MolecularPermutationClassifier subclass object.
std	character to select standardization alternative "none" (default), "scale" and "robust" as in genefu original implementation, plus the suggested "median" if many subjects are available.
verbose	should the user feedback be displayed? By default value is "verbose" global option parameter, if present, or FALSE otherwise.

Value

a PAM50 object with the updated slots:

@exprs	updated matrix with the used std parameter.
@classification	$subtype subject named factor with all classifier possible levels, i.e, "Basal", "Her2", "LumA", "LumB" and "Normal". $probability numeric matrix with subtype class probability for each subject, as in genefu, obtained as the positive proportion of correlation explained by each subtype. $correlation numeric matrix with Spearman's rho correlation of each subject to the corresponding PAM50 subtypes.

Author(s)

Cristobal Fresno [e-mail], German A. Gonzalez [e-mail], Andrea S. Llera [e-mail] and Elmer Andres Fernandez [e-mail]

References

1. Haibe-Kains B, Schroeder M, Bontempi G, Sotiriou C and Quackenbush J, 2014, genefu: Relevant Functions for Gene Expression Analysis, Especially in Breast Cancer. R package version 1.16.0, www.pmgenomics.ca/bhklab/

2. Perou CM, Sorlie T, Eisen MB, et al., 2000, Molecular portraits of human breast tumors. Nature 406:747-752.

3. Perou CM, Parker JS, Prat A, Ellis MJ, Bernard PB., 2010, Clinical implementation of the intrinsic subtypes of breast cancer, The Lancet Oncology 11(8):718-719.

See Also

PAM50 for a complete example.

Other PAM50: as, filtrate,PAM50-method, pam50centroids, permutate,PAM50-method, subjectReport,PAM50-method, subtypes,PAM50-method

Examples

##Using pam50centroids package example data
data(pam50centroids)

##Get the original PAM50 calls using genefu implementation 
pam50centroids<-classify(pam50centroids, std="none", verbose=TRUE)  
classification(pam50centroids)

Example output

Loading required package: genefu
Loading required package: survcomp
Loading required package: survival
Loading required package: prodlim
Loading required package: mclust
Package 'mclust' version 5.4.3
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: impute
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, basename, cbind, colMeans, colSums, colnames,
    dirname, 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")'.

No methods found in package 'BiocGenerics' for request: 'unlist' when loading 'pbcmc'
Enforcing filtrate(object)...
Keeping only annotated EntrezGene.ID genes
Keeping only PAM50 available genes.
Getting PAM50 subtypes...
50/50 probes are used for clustering
no standardization of the gene expressions
$subtype
 Basal   Her2   LumA   LumB Normal 
 Basal   Her2   LumA   LumB Normal 
Levels: Basal Her2 LumA LumB Normal

$probability
            Basal      Her2      LumA      LumB    Normal
Basal  0.89431418 0.0000000 0.0000000 0.0000000 0.1056858
Her2   0.00000000 0.6822947 0.0000000 0.3177053 0.0000000
LumA   0.00000000 0.0000000 0.6823842 0.0000000 0.3176158
LumB   0.00000000 0.3177053 0.0000000 0.6822947 0.0000000
Normal 0.07462325 0.0000000 0.2939143 0.0000000 0.6314624

$correlation
            Basal       Her2       LumA       LumB     Normal
Basal   1.0000000 -0.1461224 -0.6492677 -0.3604802  0.1181753
Her2   -0.1461224  1.0000000 -0.3813205  0.4656423 -0.6217047
LumA   -0.6492677 -0.3813205  1.0000000 -0.2027851  0.4654502
LumB   -0.3604802  0.4656423 -0.2027851  1.0000000 -0.7635534
Normal  0.1181753 -0.6217047  0.4654502 -0.7635534  1.0000000

pbcmc documentation built on Nov. 1, 2018, 2:09 a.m.