Estimate simulation parameters for the Splat simulation from a real dataset. See the individual estimation functions for more details on how this is done.

splatEstimate(counts, params = newSplatParams())

# S3 method for SingleCellExperiment
splatEstimate(counts,
  params = newSplatParams())

# S3 method for matrix
splatEstimate(counts, params = newSplatParams())

Arguments

counts

either a counts matrix or a SingleCellExperiment object containing count data to estimate parameters from.

params

SplatParams object to store estimated values in.

Value

SplatParams object containing the estimated parameters.

See also

Examples

# Load example data library(scater) data("sc_example_counts") params <- splatEstimate(sc_example_counts) params
#> A Params object of class SplatParams #> Parameters can be (estimable) or [not estimable], 'Default' or 'NOT DEFAULT' #> #> Global: #> (GENES) (CELLS) [Seed] #> 2000 40 298655 #> #> 28 additional parameters #> #> Batches: #> [BATCHES] [BATCH CELLS] [Location] [Scale] #> 1 40 0.1 0.1 #> #> Mean: #> (RATE) (SHAPE) #> 0.0032639148887191 0.419304527025529 #> #> Library size: #> (LOCATION) (SCALE) (Norm) #> 12.7053037408488 0.58910919018286 FALSE #> #> Exprs outliers: #> (PROBABILITY) (LOCATION) (SCALE) #> 0.00623376623376623 4.22280669039478 0.422108697251885 #> #> Groups: #> [Groups] [Group Probs] #> 1 1 #> #> Diff expr: #> [Probability] [Down Prob] [Location] [Scale] #> 0.1 0.5 0.1 0.4 #> #> BCV: #> (COMMON DISP) (DOF) #> 3.21969047393022 14.7262017878812 #> #> Dropout: #> [Type] (MIDPOINT) (SHAPE) #> none 5.00420976858168 -0.652889139821156 #> #> Paths: #> [From] [Length] [Skew] [Non-linear] [Sigma Factor] #> 0 100 0.5 0.1 0.8 #>