Aggregate CCC Method results and by both magnitude and specificity ranks

Usage

rank_aggregate(liana_res, ...)

Arguments

liana_res

LIANA results

...

Arguments passed on to liana_aggregate

aggregate_how: way to aggregate, by default (NULL) will aggregate all passed methods with the approach specified in `liana:::.score_specs`. Alternative options are `magnitude` and `specificity`.
set_cap: Function used to set ranked cap (i.e. the value that is assigned to interactions with NA for scores); By default, this is set to "max", which is the maximum number of interactions obtained by the methods; Some methods return all possible ligand-receptor combinations for each possible source and target cell pair - i.e. the known universe of all possible interactions (based on the CCC resource)
resource: If methods are ran with multiple resources, the name of the resource of interest needs to be provided *Note* if a name is not provided, the first results based on the first resource in the list will be returned
cap: A cap can for all methods can also be manually set, then the top X interactions, based on the `specificity` scores for each method will be returned and the ranking will be carried out solely on them
get_ranks: boolean, whether to return consensus ranks for methods
get_agrank: boolean, whether to return aggregate rank using the `RobustRankAggreg` package.
.score_mode: defines the way that the methods would be aggragate. By default, we use the score of each method which reflects specificity (if available), if not e.g. the case of SCA we use it's sole scoring function. This aggregation is by default done on the basis of the list returns by `.score_mode`. Alternatively, one could pass `.score_housekeep` to obtain an aggragate of the housekeeping interactions of each method.
join_cols: columns by which different method results will be joined. NULL by default, and automatically will handle the columns depending on the methods used.

Examples

liana_path <- system.file(package = "liana")
# load testdata
testdata <- readRDS(file.path(liana_path , "testdata", "input", "testdata.rds"))
# run liana
liana_res <- liana_wrap(testdata, method=c("sca", "natmi"))
#> Expression from the `RNA` assay will be used
#> Running LIANA with `seurat_annotations` as labels!
#> Warning: 3465 genes and/or 0 cells were removed as they had no counts!
#> LIANA: LR summary stats calculated!
#> Now Running: Sca
#> Now Running: Natmi
# aggregate results from multiple methods
liana_res <- rank_aggregate(liana_res)
#> Now aggregating sca
#> Now aggregating natmi
#> Aggregating Ranks
#> Warning: Unknown method name or missing specifics for: sca
#> Now aggregating natmi
#> Aggregating Ranks