outlier_analysis: 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_analysis(grouptablist, fraction_table = NULL,
    fraction_samples_cutoff = 0.3,
    write_out_tables = FALSE, outfilepath = tempdir())

Arguments

grouptablist

table generated by the count_outliers function. NOTE that the inputted grouptablist will be deciphered to determine its content. This means that user decides to input the outliertab or aggregate tab, and the output will analyze according to what positive and negative information is contained within the table

fraction_table

DEFAULT: NULL; Input a fraction table to filter to only include features that have x an outlier.

fraction_samples_cutoff

DEFAULT: 0.3; Input a fractional cut off for the of samples that need to have an outlier for feature to be considered. ex) 10 samples in ingroup - 3 need to have an outlier for feature to be considered significant

write_out_tables

DEFAULT: FALSE; utility in function to write out each of the analyses to a separate table to whereever <outfilepath> is specfied.

outfilepath

the full string path to where the file should output to, DEFAULT is a tempdir()

Value

the analysis table with p.value, fdr, and raw data per comparison

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)

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