In MultinomialMutations/MultinomialMutations: Fast multinomial regression for large cancer mutation datasets

Overview

# Total number of counts
print(total)
# Total number of mutations
print(mut)
# Mutation rate
print(mut.rate)
# number of samples
print(nsamples)
# number of genomic positions
print(npos)
# numbers of lines with missing values
print(lines.missing)

Note that there shouldn't be any missing values in the default columns.

User-specified explanatory variables

nexp = length(explanatory)
for(i in 1:nexp){

  print("###########################################################################")
  print(paste("explanatory variable:", explanatory[i]))
  print("### distribution: ###")
  print(tab[[i]])
  print(tab.prop[[i]])

  print("### proportion missing: ###")
  print(missing.prop[[i]])

}

Default explanatory variables

# left & right
print(LR)
print(LR.prop)
# from
print(from)
print(from.prop)
# to
print(to)
print(to.prop)

MultinomialMutations/MultinomialMutations documentation built on May 22, 2019, 4:39 p.m.