fcst_mannwhit: Perform Mann-Whitney U Test On Fc Array Features

In kmorrisongr/fcan: Fc Array Analysis and Manipulation

Description

For each feature in an Fc Array data frame, perform the Mann-Whitney U (Wilcoxon Rank-Sum) test to test the null hypothesis that a randomly selected value from one population (group) will be less than or greater than a randomly selected value from a second population (group). Here, this is to test whether the two sets of samples, which should be independent (treatment group A should not have an impact on treatment group B), were selected from populations having the same distribution, and there thus being no difference in the groups.

Usage

fcst_mannwhit(fc, adj_method, alternative = "two.sided", exact = FALSE)

Arguments

fc	The Fc Array data frame. Must have two groups present.
adj_method	The method you want to use to adjust p-values. Use "none" as a passthrough.
alternative	What alternative hypothesis we're testing. Supports "two.sided", "one.sided", and "either" (result of "two.sided"/2).
exact	A boolean to control whether or not exact p-values are calculated.

Value

A vector of p-values of the same length as fccu_first_feat_col(fc):ncol(fc).

kmorrisongr/fcan documentation built on Sept. 9, 2020, 10:12 a.m.