Description Usage Arguments Value Author(s) References See Also Examples
This function generates MM2S subtype predictions for Mouse samples of interest. Users are provided the option to save this the predictions as a XLS file.
1 | MM2S.mouse(InputMatrix,parallelize,seed,dir)
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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. |
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 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 |
Deena M.A. Gendoo
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
MM2S.human
,PredictionsHeatmap
,PCARender
1 2 3 4 5 6 7 8 9 10 11 12 | # Load Mouse gene expression data
# Data contains selected samples from a heterogenous WNT Mouse model
data(WNT_Mouse_Expr)
# Generate Subtype Predictions
SubtypePreds<-MM2S.mouse(InputMatrix=WNT_Mouse_Expr[2:3],parallelize=2, seed = 12345)
# Generate Heatmap of Predictions
PredictionsHeatmap(InputMatrix=SubtypePreds$Predictions, pdf_output=TRUE,pdfheight=5,pdfwidth=5)
# Generate projections of the selected genesets from
# Mouse model onto the training set, using Principal Component Analysis (PCA)
PCARender(GSVAmatrixTesting=SubtypePreds$RankMatrixTesting,
GSVAmatrixTraining=SubtypePreds$RankMatrixTraining)
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