Stochastic Profiling of mRNA counts using HMC

• Lisa Amrhein ^[1] ; Christiane Fuchs ^[1]
  1. [1] Helmholtz Zentrum München

     Helmholtz Zentrum München

     Kreisfreie Stadt München, Alemania

     
• Localización: Proceedings of the 35th International Workshop on Statistical Modelling : July 20-24, 2020 Bilbao, Basque Country, Spain / Itziar Irigoien Garbizu (ed. lit.), Dae-Jin Lee (ed. lit.), Joaquín Martínez Minaya (ed. lit.), María Xosé Rodríguez Álvarez (ed. lit.), 2020, ISBN 978-84-1319-267-3, págs. 270-273
• Idioma: inglés
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• Resumen

  • We dissect transcriptional heterogenity from RNA sequencing counts taken from small pools of cells when single-cell data is disadvantageous. For this purpose, we extend the stochastic pro ling algorithm (Amrhein & Fuchs 2020) to discrete data. In addition, we perform Bayesian inference using Hamiltonian Monte Carlo. Our implementation uses Stan to optimize computational eciency.