Joag-Dev and Proschan [1] introduced the definition of negative association and showed that many of the well-known multivariate distributions possess the negatively associated property, for example, multivariate hypergeometric distribution, negatively correlated normal distribution, random sampling without replacement, etc.
We used the proposed model based on the multivariate hypergeometric distribution.
First, Banerjee and Zhang (2003) [ 6] integrated ChIP-chip data and gene expression data to calculate expression correlation score and designed a model to assess the significance of the TF cooperativity based on multivariate hypergeometric distribution.
We obtain the average SEP in terms of the Lauricella multivariate hypergeometric function.
A number of well-known multivariate distributions, such as a multinomial distribution, multivariate hypergeometric distribution, negatively correlated normal distribution and joint distribution of ranks, possess the NA property.
A number of well-known multivariate distributions possess the NA property, such as the multinomial distribution, multivariate hypergeometric distribution, negatively correlated normal distribution, and joint distribution of ranks.
Both scenarios converge if the number of sampled individuals is large, and, for similar expected frequencies, multivariate hypergeometric distribution presents smaller variances.
Can the approximate Beta-Poisson model be used or is it necessary to use the exact hypergeometric model?
The p-value is obtained by the hypergeometric model for sampling without replacement:.
Metacore uses a hypergeometric model to determine the significance of enrichment.
