601. casper- casper infers alternative splicing from high-throughput sequencing data both for known variants and de novo discovery. We use a Bayesian model with few assumptions, and modern model selection ideas with improved theoretical and computational properties.
602. Profile Dirichlet Process Mixtures- This package facilitates profile inference for a class of product partition models (PPM). The Dirichlet process mixture is a specific case in this class. These methods search for the maximum posterior (MAP) estimate for the cluster partition in the PPM.
606. Plot manageable subsets of data- Plotting a large data set is difficult if it does not fit into memory as a data frame, so we introduce more efficient data structures and alternative plot functions that work with large data.