MM2S (version 1.0.6)

PredictionsBarplot: Stacked Barplot of MM2S Subtype Predictions for Given Samples

Description

This function generates a stacked barplot of MM2S subtype predictions for samples of interest. Users are provided the option to save this heatmap as a PDF file.

Usage

PredictionsBarplot(InputMatrix,pdf_output,pdfheight,pdfwidth)

Arguments

InputMatrix

Matrix with samples in rows, and columns with MM2S percentage predictions for each subtype (Gr4,Gr3,Sonic hedgehog (SHH),Wingless (WNT), and Normal)

pdf_output

Option to save the heatmap as a PDF file

pdfheight

User-defined specification for PDF height size

pdfwidth

User-defined specification for PDF width size

Value

Generated Stacked Barplot of MM2S subtype predictions. Samples are in columns. Stacks are reflective of prediction percentages across MB subtypes for a given sample.

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

Examples

# NOT RUN {
# Generate heatmap from already-computed predictions for the GTML Mouse Model
## load computed MM2S predictions for GTML mouse model
data(GTML_Mouse_Preds)
## Generate Barplot
PredictionsBarplot(InputMatrix=GTML_Mouse_Preds, pdf_output=TRUE,pdfheight=5,pdfwidth=5)
# }
# NOT RUN {
# Generate heatmap after running raw expression data through MM2S
# load Mouse gene expression data for the potential WNT mouse model
data(WNT_Mouse_Expr)
SubtypePreds<-MM2S.mouse(InputMatrix=WNT_Mouse_Expr[2:3],parallelize=1, seed = 12345)
# Generate Heatmap
PredictionsBarplot(InputMatrix=SubtypePreds$Predictions,pdf_output=TRUE,pdfheight=5,pdfwidth=5)
# }