MISO is a new open-source Lab Information Management System (LIMS) under development at TGAC, specifically designed for tracking next-generation sequencing experiments.
MISO (Mixture of Isoforms) 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 particular isoform.