MSIseq.train: Build Microsatellite Instability Classification Model with...

In MSIseq: Assess Tumor Microsatellite Instability with a Decision Tree Classifier from Exome Somatic Mutations

Description

This function generate a detector for MSI status based on the mutation information in the mutationNum parameter.

Usage

MSIseq.train(mutationNum, classification, cancerType = NULL)

Arguments

mutationNum	A data frame output from Compute.input.variables, which containing 9 variables: T.sns, S.sns, T.ind, S.ind, T, S, Ratio.sns, Ratio.ind, Ratio.
classification	A data frame with two columns: Tumor_Sample_Barcode (tumor ID) and the corresponding MSI_status. Check NGStrainclass for detail.
cancerType	A data frame with two columns: Tumor_Sample_Barcode (tumor ID) and the corresponding cancer_type. Check NGStraintype for detail.

Details

This function builds and evaluates a decision tree model from mutationNum.

Value

A Weka_classifier object: a decision tree model built with the 'RWeka' function J48()

Author(s)

Mini Huang

References

Kurt Hornik, Christian Buchta, Achim Zeileis (2009) Open-Source Machine Learning: R Meets Weka. Computational Statistics, 24(2), 225-232.

See Also

MSIseq.classify, Compute.input.variables

Examples

## load sample data (train.mutationNum, NGStraintype, 
## NGStrainclass)

data(train.mutationNum)
data(NGStrainclass)
data(NGStraintype)

## create NGSclassifier with traindata
## note that this is a built-in classifier, which can be directly used 
## if you do not have your own training data to create a classifier

NGSclassifier<-MSIseq.train(mutationNum = train.mutationNum, 
  classification=NGStrainclass, cancerType=NGStraintype)

Example output

Loading required package: IRanges
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colMeans, colSums, colnames,
    dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
    intersect, is.unsorted, lapply, lengths, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following object is masked from 'package:base':

    expand.grid

Loading required package: RWeka
Loading required package: rJava
Loading required package: R.utils
Loading required package: R.oo
Loading required package: R.methodsS3
R.methodsS3 v1.7.1 (2016-02-15) successfully loaded. See ?R.methodsS3 for help.
R.oo v1.22.0 (2018-04-21) successfully loaded. See ?R.oo for help.

Attaching package: 'R.oo'

The following object is masked from 'package:rJava':

    clone

The following object is masked from 'package:IRanges':

    trim

The following objects are masked from 'package:methods':

    getClasses, getMethods

The following objects are masked from 'package:base':

    attach, detach, gc, load, save

R.utils v2.8.0 successfully loaded. See ?R.utils for help.

Attaching package: 'R.utils'

The following object is masked from 'package:utils':

    timestamp

The following objects are masked from 'package:base':

    cat, commandArgs, getOption, inherits, isOpen, parse, warnings

5 fold cross validation result: 98.61496

MSIseq documentation built on May 2, 2019, 7:23 a.m.