Run selected set of methods and average results

Usage

deconvolute_combined(
  methyl_set,
  array = c("450k", "EPIC"),
  methods,
  scale_results = FALSE,
  ...
)

Arguments

methyl_set: A minfi MethylSet
array: type of methylation array that was used. possible options are '450k' and 'EPIC'
methods: list of methods (>1) that will be applied to the methyl set
scale_results: Whether the deconvolution results should be rescaled. Negative values will be set to 0, and the estimates will be normalized to sum to 1 per sample. Defaults to FALSE.
...: Additional parameters, passed to the algorithm used. See individual method documentations for details.

Value

dataframe with results of all selected methods as well as the combined estimates

Examples


ex_data <- minfiData::MsetEx

result <- deconvolute_combined(ex_data, methods=c('epidish','houseman'))
#> Warning: 12 NA values detected in your beta matrix. Replacing them with 0.5.
#> RPC was chosen as default for "mode"
#> blood was chosen as default for "reference"
#> Starting EpiDISH deconvolution with mode RPC ...
#> 450k was chosen as default for "array"
#> Blood was chosen as default for "compositeCellType"
#> IlluminaHumanMethylationEPIC was chosen as default for "referencePlatform"
#> IDOL was chosen as default for "probeSelect"
#> [estimateCellCounts2] The function will assume that no preprocessing has been performed. Using 'preprocessQuantile' in prenormalized data is experimental and it should only be run under the user responsibility
#> Loading required package: FlowSorted.Blood.EPIC
#> Loading required package: ExperimentHub
#> Loading required package: AnnotationHub
#> Loading required package: BiocFileCache
#> Loading required package: dbplyr
#> 
#> Attaching package: ‘AnnotationHub’
#> The following object is masked from ‘package:Biobase’:
#> 
#>     cache
#> see ?FlowSorted.Blood.EPIC and browseVignettes('FlowSorted.Blood.EPIC') for documentation
#> downloading 1 resources
#> retrieving 1 resource
#> loading from cache
#> Loading required package: IlluminaHumanMethylationEPICmanifest
#> [convertArray] Casting as IlluminaHumanMethylationEPIC
#> [estimateCellCounts2] Combining user data with reference (flow sorted) data.
#> Warning: NAs introduced by coercion
#> [estimateCellCounts2] Processing user and reference data together.
#> [preprocessQuantile] Mapping to genome.
#> Loading required package: IlluminaHumanMethylationEPICanno.ilm10b4.hg19
#> [preprocessQuantile] Fixing outliers.
#> [preprocessQuantile] Quantile normalizing.
#> [estimateCellCounts2] Using IDOL L-DMR probes for composition estimation.
#> [estimateCellCounts2] Estimating proportion composition (prop), if you provide cellcounts those will be provided as counts in the composition estimation.