The 'proDAFit' object overwrites the dollar function to make it easy
to call functions to access values inside the object. This has the
advantage that it is very easy to discover the relevant methods
but nonetheless have an isolated implementation. Unlike the
`@` operator which directly accesses the underlying implementation,
the `$` operator only exposes a limited set of functions
abundances
hyper_parameters
feature_parameters
coefficients
convergence
design
reference_level
result_names
coefficient_variance_matrices
colData
rowData
# S3 method for proDAFit .DollarNames(x, pattern = "") # S4 method for proDAFit $(x, name) # S4 method for proDAFit $(x, name) <- value
| x | an object of class 'proDAFit' produced by |
|---|---|
| pattern | the regex pattern that is provided by the IDE |
| name | one of the functions listed above |
| value | Warning: modifying the content of a 'proDAFit' object is not allowed |
whatever the function called name returns.
accessor_methods for more documentation on the accessor functions.
syn_data <- generate_synthetic_data(n_proteins = 10) fit <- proDA(syn_data$Y, design = syn_data$groups) # The two styles are identical design(fit)#> Condition_1 Condition_2 #> Condition_1-1 1 0 #> Condition_1-2 1 0 #> Condition_1-3 1 0 #> Condition_2-1 0 1 #> Condition_2-2 0 1 #> Condition_2-3 0 1 #> attr(,"assign") #> [1] 1 1 #> attr(,"contrasts") #> attr(,"contrasts")$x_ #> [1] "contr.treatment" #>fit$design#> Condition_1 Condition_2 #> Condition_1-1 1 0 #> Condition_1-2 1 0 #> Condition_1-3 1 0 #> Condition_2-1 0 1 #> Condition_2-2 0 1 #> Condition_2-3 0 1 #> attr(,"assign") #> [1] 1 1 #> attr(,"contrasts") #> attr(,"contrasts")$x_ #> [1] "contr.treatment" #># More functions fit$abundances#> Condition_1-1 Condition_1-2 Condition_1-3 Condition_2-1 #> protein_1 24.07919 23.42556 23.94491 24.21937 #> protein_2 18.61085 18.18919 NA NA #> protein_3 NA NA NA NA #> protein_4 NA 18.35705 17.45826 NA #> protein_5 21.94793 20.08355 24.01483 21.14165 #> protein_6 23.71996 24.34934 24.07880 23.33419 #> protein_7 NA NA 17.72383 18.07316 #> protein_8 21.88006 21.28270 21.53463 21.96805 #> protein_9 20.88883 21.35111 21.41965 21.15165 #> protein_10 NA NA NA NA #> Condition_2-2 Condition_2-3 #> protein_1 23.50432 24.27628 #> protein_2 18.65685 NA #> protein_3 NA NA #> protein_4 NA NA #> protein_5 21.54833 21.39306 #> protein_6 24.23279 23.77613 #> protein_7 NA NA #> protein_8 21.56534 21.77661 #> protein_9 21.78433 21.05557 #> protein_10 NA NA