README.md

In hint: Tools for Hypothesis Testing Based on Hypergeometric Intersection Distributions

hint

Summary

hint is an R package for performing hypothesis testing based on Hypergeometric Intersection distributions. For example if you had three gene sets arising from three separate experiments with x genes shared between the three, you could determine the probability of arriving at this intersection size by chance. See the companion paper for more information.

Installation

install.packages("hint")

Usage

library(hint)

## The probability of an intersection of size 5 or greater 
## when sampling 15, 8, and 7 balls from three urns 
## each with 1 ball in each of 29 categories.

phint(29, c(15, 8, 7), vals = 5)
  v        cum.p
1 5 0.0002289938

## Formalising a hypothesis test using 'hint.test'.
# Categories given in the first column.
# Numbers of balls in each category given in subsequent columns: each column representing an urn.
dd <- data.frame(categories = letters[1:20], 
                 urn1_count = rep(1,20), 
                 urn2_count = rep(1,20))
tt <- hint.test(dd, letters[1:9], 
                letters[4:15], alternative = "greater")
print(tt)

Hypergeometric intersection test

Parameters:
 n  a  b  q  v 
20  9 12  0  6 

 P(X >= v)  =  0.4649917 

plot(tt)

## Allow duplicates in the second urn.
dd <- data.frame(letters[1:20], 
                 rep(1,20), 
                 c(rep(1,4), rep(2,16)))
tt <- hint.test(dd, letters[1:9], 
                letters[9:14], alternative = "less")
print(tt)

Hypergeometric intersection test

Parameters:
 n  a  b  q  v 
20  9  6 16  1 

 P(X <= v)  =  0.1596769

References

Kalinka (2013). The probability of drawing intersections: extending the hypergeometric distribution. arXiv.1305.0717

hint documentation built on Feb. 2, 2022, 5:10 p.m.