prioritize | R Documentation |
Metabolic features are ranked based on AVA, and q-value and effect size of differential abundance. The harmonic mean of these three ranks is calculated and used as the meta-rank to prioritize potentially bioactive features in a phenotype (or condition). Top-ranked features have good relative abundance, and are significantly perturbed in the specified environment/phenotype.
prioritize(se, mod.assn, mac.ava, mac.qval, mac.es)
se |
SummarizedExperiment object created using Macarron::prepInput() |
mod.assn |
the output of Macarron::findMacMod() |
mac.ava |
the output of Macarron::calAVA() |
mac.qval |
the output of Macarron::calQval() |
mac.es |
the output of Macarron::calES() |
mac.result - metabolic features listed according to priority
prism_abundances = system.file("extdata", "demo_abundances.csv", package="Macarron")
abundances_df = read.csv(file = prism_abundances, row.names = 1)
prism_annotations = system.file("extdata", "demo_annotations.csv", package="Macarron")
annotations_df = read.csv(file = prism_annotations, row.names = 1)
prism_metadata = system.file("extdata", "demo_metadata.csv", package="Macarron")
metadata_df = read.csv(file = prism_metadata, row.names = 1)
met_taxonomy = system.file("extdata", "demo_taxonomy.csv", package="Macarron")
taxonomy_df = read.csv(file = met_taxonomy)
mbx <- Macarron::prepInput(input_abundances = abundances_df,
input_annotations = annotations_df,
input_metadata = metadata_df)
w <- Macarron::makeDisMat(se = mbx)
modules.assn <- Macarron::findMacMod(se = mbx,
w = w,
input_taxonomy = taxonomy_df)
mets.ava <- Macarron::calAVA(se = mbx,
mod.assn = modules.assn)
mets.qval <- Macarron::calQval(se = mbx,
mod.assn = modules.assn)
mets.es <- Macarron::calES(se = mbx,
mac.qval = mets.qval)
mets.prioritized <- Macarron::prioritize(se = mbx,
mod.assn = modules.assn,
mac.ava = mets.ava,
mac.qval = mets.qval,
mac.es = mets.es)
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