SubpathwayMatrix: Get metabolic subpathway activity matrix
In hanjunwei-lab/crmSubpathway: Identify cancer-related metabolic subpathways

Description Usage Arguments Details Examples

Get metabolic subpathway activity matrix.

SubpathwayMatrix(
  Gexp,
  Subpathway.list,
  method = "gsva",
  kcdf = "Gaussian",
  min.sz = 1,
  max.sz = Inf,
  parallel.sz = 0
)

`Gexp`	Matrix of gene expression values (rows are genes, columns are samples).
`Subpathway.list`	The subpathway list data. We have stored the processed human metabolic subpathway data set in variable 'Metspwlist'. Users can also set their own data set of subpathways.
`method`	Method to employ in the estimation of subpathway enrichment scores per sample. By default this is set to 'gsva' (Hänzelmann et al, 2013) and other options are 'ssgsea' (Barbie et al, 2009).
`kcdf`	Character string denoting the kernel to use during the non-parametric estimation of the cumulative distribution function of expression levels across samples when 'spw.score.method="gsva"'. By default, 'kcdf="Gaussian"' which is suitable when input expression values are continuous, such as microarray fluorescent units in logarithmic scale, RNA-seq log-CPMs, log-RPKMs or log-TPMs. When input expression values are integer counts, such as those derived from RNA-seq experiments, then this argument should be set to 'kcdf="Poisson"'.
`min.sz`	Removes subpathways that contain fewer genes than 'spw.min.sz' (default: 10).
`max.sz`	Removes subpathways that contain more genes than 'spw.max.sz' (default: Inf).
`parallel.sz`	Number of processors to use when doing the calculations in parallel (default value: 1). If parallel.sz=0, then it will use all available core processors unless we set this argument with a smaller number.

SubpathwayMatrix

Our method assesses the relative enrichment of metabolic subpathways across samples using a non-parametric approach. Conceptually, this method transforms a p-gene by n-sample gene expression matrix into a g-subpathway by n-sample metabolic subpathway enrichment matrix.

library(GSVA)
library(parallel)
# Get the dataset of metabolic subpathways we have processed.
Metspwlist<-get("Metspwlist")
# Get the gene expression profile of the case.
Geneexp<-get("Geneexp")
Spwmatrix<-SubpathwayMatrix(Geneexp,Metspwlist)