MISO (Mixture of
- MISO is a probabilistic framework that quantitates the
expression level of alternatively spliced genes from RNA-Seq data,
and identifies differentially regulated isoforms or exons across
samples. By modeling the generative process by which reads are
produced from isoforms in RNA-Seq, the MISO model uses Bayesian
inference to compute the probability that a read originated from a
MISO treats the expression level of a set of isoforms as a random variable and estimates a distribution over the values of this variable. The estimation algorithm is based on sampling, and falls in the family of techniques known as Markov Chain Monte Carlo (“MCMC”).