MM2S (version 1.0.6)

MM2S.human: MM2S Prediction of Human Medulloblastoma Samples

Description

This function generates MM2S subtype predictions for human samples of interest. Users are provided the option to save this the predictions as a XLS file.

Usage

MM2S.human(InputMatrix,parallelize,seed,dir)

Arguments

InputMatrix

Matrix containing normalized gene expression data, with genes in rows and samples in columns. Gene IDs MUST be represented as Entres Gene IDs.

parallelize

Option to set number of cores to run ssGSEA calculations in parallel. Default is 1 (no parallelization)

seed

[integer] has to be specified by the user.

dir

Option to save MM2S subtype predictions only if the user wants to and specifies the dir.

Value

Predictions

MM2S Percent Confidence Predictions of Human Subtypes (Group3, Group4, Normal, Sonic hedgehog (SHH),Wingless (WNT)) for a given sample.

MM2S_Subtype

List of Sample names the designated Human Medulloblastoma (MB) subtype from MM2S classification.

RankMatrixTesting

ssGSEA rank matrix of the test data, using selected genesets common between the test data and training set. These genesets are based on a filtered list using the top24 common genesets, for each subtype

RankMatrixTraining

ssGSEA rank matrix of the trained MM2S human data, using selected genesets common between the test data and training set. These genesets are based on a filtered list using the top24 common genesets, for each subtype

References

Gendoo, D. M., Smirnov, P., Lupien, M. & Haibe-Kains, B. Personalized diagnosis of medulloblastoma subtypes across patients and model systems. Genomics, doi:10.1016/j.ygeno.2015.05.002 (2015)

Manuscript URL: http://www.sciencedirect.com/science/article/pii/S0888754315000774

See Also

MM2S.mouse,PredictionsHeatmap,PCARender

Examples

# NOT RUN {
 #load Human gene expression data containing selected samples from GSE37418
 data(Human_Cho_Expr)
 SubtypePreds<-MM2S.human(InputMatrix=Human_Cho_Expr[1:3],parallelize=2, seed = 12345)

 #Generate Heatmap of Predictions
 PredictionsHeatmap(InputMatrix=SubtypePreds$Predictions, pdf_output=TRUE,pdfheight=5,pdfwidth=5)
# }