Filter MiDAS object by features

Filter MiDAS object by features

filterByVariables(object, experiment, variables)

Arguments

object

MiDAS object.

experiment

String specifying experiment.

variables

Character vector specifying features to select.

Value

Filtered MiDAS object.

Examples

filterByVariables(object = MiDAS_tut_object,
                  experiment = "hla_alleles",
                  variables = c("A*25:01", "A*26:01", "B*07:02"))
#> A MiDAS object of 10 listed
#>  experiments with user-defined names and respective classes.
#>  Containing an ExperimentList class object of length 10:
#>  [1] hla_alleles: SummarizedExperiment with 3 rows and 1000 columns
#>  [2] hla_aa: SummarizedExperiment with 1223 rows and 1000 columns
#>  [3] hla_g_groups: SummarizedExperiment with 46 rows and 1000 columns
#>  [4] hla_supertypes: SummarizedExperiment with 12 rows and 1000 columns
#>  [5] hla_NK_ligands: SummarizedExperiment with 5 rows and 1000 columns
#>  [6] kir_genes: SummarizedExperiment with 16 rows and 1000 columns
#>  [7] kir_haplotypes: SummarizedExperiment with 6 rows and 1000 columns
#>  [8] hla_kir_interactions: SummarizedExperiment with 29 rows and 1000 columns
#>  [9] hla_divergence: matrix with 4 rows and 1000 columns
#>  [10] hla_het: SummarizedExperiment with 9 rows and 1000 columns
#> Functionality:
#>  experiments() - obtain the ExperimentList instance
#>  colData() - the primary/phenotype DataFrame
#>  sampleMap() - the sample coordination DataFrame
#>  `$`, `[`, `[[` - extract colData columns, subset, or experiment
#>  *Format() - convert into a long or wide DataFrame
#>  assays() - convert ExperimentList to a SimpleList of matrices
#>  exportClass() - save data to flat files