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

Journal Article (Journal Article)

Single-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. We 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. We tested BayFish on synthetic data and smFISH measurements of the neuronal activity-inducible gene Npas4 in primary neurons.

Full Text

Duke Authors

Cited Authors

  • Gómez-Schiavon, M; Chen, L-F; West, AE; Buchler, NE

Published Date

  • September 4, 2017

Published In

Volume / Issue

  • 18 / 1

Start / End Page

  • 164 -

PubMed ID

  • 28870226

Pubmed Central ID

  • PMC5582403

Electronic International Standard Serial Number (EISSN)

  • 1474-760X

Digital Object Identifier (DOI)

  • 10.1186/s13059-017-1297-9


  • eng

Conference Location

  • England