Subject level clustering using a negative binomial model for small transcriptomic studies

Unsupervised clustering represents one of the most widely applied methods in analysis of highthroughput ‘omics data. A variety of unsupervised model-based or parametric clustering methods and nonparametric clustering methods have been proposed for RNA-seq count data, most of which perform well for large samples, e.g. N ≥ 500.