IWTomics-package {IWTomics} | R Documentation

## Interval-Wise Testing for Omics Data

### Description

Implementation of the Interval-Wise Testing for "Omics" data, an extended version of the Interval-Wise Testing for functional data presented in Pini and Vantini (2017). This inferential procedure tests for differences in "Omics" data between two groups of genomic regions (or between a group of genomic regions and a reference curve), and does not require fixing location and scale at the outset.

### Author(s)

Marzia A Cremona, Alessia Pini, Francesca Chiaromonte, Simone Vantini

Maintainer: Marzia A Cremona <mac78@psu.edu>

### References

A Pini and S Vantini (2017). Interval-Wise Testing for functional data. Journal of Nonparametric Statistics.

### Examples

    ## -------------------------------------------------------------------------------------------
    ## -------------------------------------------------------------------------------------------
    ## EXAMPLE ON REAL DATA
    ## -------------------------------------------------------------------------------------------
    ## -------------------------------------------------------------------------------------------
    ## ETn Recombination hotspots data
    ## Two region datasets:
    ## ETns fixed 64-kb flanking regions and 64-kb control regions in mouse
    ## One feature measured in 1-kb windows:
    ## Recombination hotspots content
    ## ?ETn_example for details on the dataset
    data(ETn_example)
    ETn_example

    ## -------------------------------------------------------------------------------------------
    ## PLOT DATA
    ## -------------------------------------------------------------------------------------------
    ## Plot the pointwise boxplot and averages of the curves in ETn and control regions
    ## (note that the box of the pointwise boxplot is zero, but the average is not)
    plot(ETn_example)

    ## -------------------------------------------------------------------------------------------
    ## PERFORM THE TEST
    ## -------------------------------------------------------------------------------------------
    ## Two sample test to compare recombination hotspots
    ## in ETn regions vs control regions
    ETn_test=IWTomicsTest(ETn_example,
                         id_region1='ETn_fixed',id_region2='Control')
    ## Adjusted p-value
    adjusted_pval(ETn_test)

    ## Plotting the test results
    plotTest(ETn_test)

    ## Adjusted p-value lowering the scale of the test
    adjusted_pval(ETn_test,scale_threshold=10)

    ## Plotting the test results, lowering the scale of the test
    plotTest(ETn_test,scale_threshold=10)

    ## Summary plot of the two sample test
    ## x11(12,2)
    plotSummary(ETn_test,groupby='feature',scale_threshold=10,
                align_lab='Integration site')

    ## -------------------------------------------------------------------------------------------
    ## -------------------------------------------------------------------------------------------
    ## EXAMPLE ON SIMULATED DATA
    ## -------------------------------------------------------------------------------------------
    ## -------------------------------------------------------------------------------------------
    examples_path <- system.file("extdata",package="IWTomics")
    ## Four region datasets:
    ## three different types of elements and one control
    datasets=read.table(file.path(examples_path,"datasets.txt"),
                        sep="\t",header=TRUE,stringsAsFactors=FALSE)
    datasets
    ## Two different features measured in all four types regions
    features_datasetsTable=read.table(file.path(examples_path,"features_datasetsTable.txt"),
                                      sep="\t",header=TRUE,stringsAsFactors=FALSE)
    features_datasetsTable

    ## -------------------------------------------------------------------------------------------
    ## GET DATA AND PLOT
    ## -------------------------------------------------------------------------------------------
    ## Get genomic regions for the four region datasets,
    ## and the two features from Table files for each region dataset
    regionsFeatures=IWTomicsData(datasets$regionFile,features_datasetsTable[,3:6],'center',
                                datasets$id,datasets$name,
                                features_datasetsTable$id,features_datasetsTable$name,
                                path=file.path(examples_path,'files'))

    ## Plot the pointwise boxplot of the curves in the different region datasets
    plot(regionsFeatures)

    ## -------------------------------------------------------------------------------------------
    ## PERFORM THE TEST
    ## -------------------------------------------------------------------------------------------
    ## Two sample test for the two features in the comparisons
    ## 'elem1' vs 'control', 'elem2' vs 'control'
    ## and 'elem3' vs 'control'
    regionsFeatures_test=IWTomicsTest(regionsFeatures,id_region1=c('elem1','elem2','elem3'),
                                                      id_region2=c('control','control','control'))
    ## Adjusted p-value for each comparison and each feature
    adjusted_pval(regionsFeatures_test)

    ## Plotting the results of the two sample test
    plotTest(regionsFeatures_test)

    ## Summary plot of the two sample tests
    ## x11(10,5)
    plotSummary(regionsFeatures_test,groupby='feature',align_lab='Center')

[Package IWTomics version 1.18.0 Index]