fetchResults <- function(object, assay, item) {
if(!is(object = object, class2 = 'IBRAP')) {
stop('object must be of class IBRAP \n')
}
if(!is.character(assay)) {
stop('assay must be character string(s) \n')
}
for(x in assay) {
if(!x %in% names(object@methods)) {
stop(paste0('assay: ', x, 'does not exist\n'))
}
}
if(!is.character(item)) {
stop('item must be character string(s) \n')
}
if(item %in% c('counts','normalised','norm.scaled')) {
return(object@methods[[assay]][[item]])
} else if (item=='highly.variable.genes') {
return(object@methods[[assay]]@highly.variable.genes)
} else if (item %in% names(object@methods[[assay]]@computational_reductions)) {
return(object@methods[[assay]]@computational_reductions[[item]])
} else if (item %in% names(object@methods[[assay]]@integration_reductions)) {
return(object@methods[[assay]]@integration_reductions[[item]])
} else if (item %in% names(object@methods[[assay]]@visualisation_reductions)) {
return(object@methods[[assay]]@visualisation_reductions[[item]])
} else if (item %in% names(object@methods[[assay]]@neighbours)) {
return(object@methods[[assay]]@neighbours[[item]])
} else if (item %in% names(object@methods[[assay]]@neighbours)) {
return(object@methods[[assay]]@neighbours[[item]])
} else if (item %in% names(object@methods[[assay]]@cluster_assignments)) {
return(object@methods[[assay]]@cluster_assignments[[item]])
} else if ('clustering' %in% names(object@methods[[assay]]@benchmark_results)) {
return(object@methods[[assay]]@benchmark_results$clustering[[item]])
}
else if ('clustering' %in% names(object@methods[[assay]]@benchmark_results)) {
return(object@methods[[assay]]@benchmark_results$clustering[[item]])
} else {
stop('item cannot be found \n')
}
}
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