outlier_heatmap: With the grouptablist generated by count_outliers - run...

Description Usage Arguments Value Examples

View source: R/outlier_analysis_functions.R

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

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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

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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)

blacksheepr documentation built on Nov. 8, 2020, 7:57 p.m.