convert_to_ {decoupleR} | R Documentation |
Convert a long-format network to the suggested standard for the
specified run_{statistic}()
. If the default parameters are not modified,
then the function sets its own null values for those columns.
convert_to_(network) convert_to_scira(network, .source, .target, .mor = NULL) convert_to_pscira(network, .source, .target, .mor = NULL) convert_to_mean(network, .source, .target, .mor = NULL, .likelihood = NULL) convert_to_viper(network, .source, .target, .mor = NULL, .likelihood = NULL) convert_to_gsva(network, .source, .target) convert_to_ora(network, .source, .target)
network |
Tibble or dataframe with edges and it's associated metadata. |
.source |
Column with source nodes. |
.target |
Column with target nodes. |
.mor |
Column with edge mode of regulation (i.e. mor). |
.likelihood |
Column with edge likelihood. |
convert_to_
Return same as input.
convert_to_gsva()
Return a list of regulons suitable for GSVA::gsva()
.
convert_to_mean()
Return a tibble with four columns: tf
, target
, mor
and likelihood
.
convert_to_ora()
Return a named list of regulons; tf with associated targets.
convert_to_pscira()
Returns a tibble with three columns: tf
, target
and mor
.
convert_to_scira()
Returns a tibble with three columns: tf
, target
and mor
.
convert_to_viper()
Return a list of regulons suitable for viper::viper()
inputs_dir <- system.file("testdata", "inputs", package = "decoupleR") network <- readRDS(file.path(inputs_dir, "input-dorothea_genesets.rds")) convert_to_(network) convert_to_gsva(network, tf, target) convert_to_mean(network, tf, target, mor, likelihood) convert_to_ora(network, tf, target) convert_to_pscira(network, tf, target, mor) convert_to_scira(network, tf, target, mor) convert_to_viper(network, tf, target, mor, likelihood)