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Catalina Vallejos edited this page Oct 11, 2017 · 8 revisions

This page illustrates the usage of BASiCS based on a built-in data example. This consists of a SingleCellExperiment object that already contains all the necessary information. See here for input preparation instructions.

Data <- makeExampleBASiCS_Data()

Parameter estimation is performed using the BASiCS_MCMC function. Essential parameters for running this algorithm are:

  • N: total number of iterations
  • Thin: length of the thining period (i.e. only every Thin iterations will be stored in the output of the BASiCS_MCMC)
  • Burn: length of burn-in period (i.e. the initial Burn iterations that will be discarded from the output of the BASiCS_MCMC)

If the optional parameter PrintProgress is set to TRUE, the R console will display the progress of the MCMC algorithm. For other optional parameters refer to help(BASiCS_MCMC).

Chain <- BASiCS_MCMC(Data = Data, N = 20000, Thin = 20, Burn = 10000, 
                     PrintProgress = FALSE)

Once the MCMC sampler has run, it is important to assess the convergence of the chain.

References: Vallejos et al (2015) PLoS Computational Biology; Vallejos et al (2016) Genome Biology; Eling et al (2018) Cell Systems

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