BayFish: Bayesian inference of transcription dynamics from population snapshots of single-molecule RNA FISH in single cells

screen-shot-2017-09-12-at-10-49-05-amSingle-molecule RNA fluorescence in situ hybridization (smFISH) provides unparalleled resolution in the measurement of the abundance and localization of nascent and mature RNA transcripts in fixed, single cells. Mariana developed a computational pipeline (BayFish) to infer the kinetic parameters of gene expression from smFISH data at multiple time points after gene induction. Given an underlying model of gene expression, BayFish uses a Monte Carlo method to estimate the Bayesian posterior probability of the model parameters and quantify the parameter uncertainty given the observed smFISH data. This has been a fun and fruitful collaboration with the Anne West lab in Neuroscience at Duke!

Gomez-Schiavon M, Chen LF, West AE, Buchler NE.  BayFish: Bayesian inference of transcription dynamics from population snapshots of single-molecule RNA FISH in single cells.  Genome Biology 18: 164 (2017)