outlier_heatmap {blacksheepr} | R Documentation

## With the grouptablist generated by count_outliers - run through and run a fisher exact test to get the p.value for the difference in outlier count for each feature in each of your comparisons

### Description

With the grouptablist generated by count_outliers - run through and run a fisher exact test to get the p.value for the difference in outlier count for each feature in each of your comparisons

### Usage

    outlier_heatmap(outlier_analysis_out, analysis_num = NULL,
        counttab, metatable, fdrcutoffvalue = 0.1)

### Arguments

`outlier_analysis_out` | the full outlier_analysis data objet
`analysis_num` | DEFAULT: NULL; if you only want to plot the heatmap for a particular analysis, enter number of that analysis
`counttab` | the raw data before outlier analysis
`metatable` | the complete metatable that was used to generate the comparisons, will be used for annotation of the heatmap
`fdrcutoffvalue` | DEFAULT: 0.1; The FDR value for significance

### Value

outputs a pdf with the heatmap in the current working directory

### Examples

    data("sample_phosphodata")
    reftable_function_out <- make_outlier_table(sample_phosphodata[1:1000,])
    outliertab <- reftable_function_out$outliertab

    data("sample_annotationdata")
    groupings <- comparison_groupings(sample_annotationdata)

    count_outliers_out <- count_outliers(groupings, outliertab,
        aggregate_features = FALSE)
    grouptablist <- count_outliers_out$grouptablist
    fractiontab <- count_outliers_out$fractiontab

    outlier_analysis_out <- outlier_analysis(grouptablist,
        fraction_table = fractiontab)

    metatable <- sample_annotationdata
    counttab <- sample_phosphodata

    hm1 <- outlier_heatmap(outlier_analysis_out, analysis_num = NULL,
        fractiontab, metatable, fdrcutoffvalue = 0.1)

[Package blacksheepr version 1.1.0 Index]