Clustering High-Throughput Transcriptome Sequencing (HTS) Data
Calculate ARI for high-dimensional data via data splits
Clustering high throughput sequencing (HTS) data
View HTSCluster User's Guide
Parameter initialization for a Poisson mixture model.
Log likelihood calculation for a Poisson mixture model
Visualize results from clustering using a Poisson mixture model
Poisson mixture model estimation and model selection
Calculate the conditional per-cluster mean of each observation
Simulate data from a Poisson mixture model
Calculate the conditional probability of belonging to each cluster in ...
Summarize results from clustering using a Poisson mixture model
A Poisson mixture model is implemented to cluster genes from high- throughput transcriptome sequencing (RNA-seq) data. Parameter estimation is performed using either the EM or CEM algorithm, and the slope heuristics are used for model selection (i.e., to choose the number of clusters).