calAVA: Calculate abundance versus anchor (AVA) of metabolic...

In biobakery/MACARRoN: Prioritization of potentially bioactive metabolic features from epidemiological and environmental metabolomics datasets

Calculate abundance versus anchor (AVA) of metabolic features.

Description

AVA of a feature is the ratio of its abundance and the most abundant metabolite in the same module i.e. the "anchor". Anchor is an annotated/known feature if available or just the most abundant metabolic feature. For every feature, mean abundance in each phenotype or condition is calculated and the maximum is considered for AVA calculation. Singletons are assigned an AVA of 1.

Usage

calAVA(se, mod.assn, metadata_variable = 1, anchor_annotation = 2)

Arguments

se	SummarizedExperiment object created using Macarron::prepInput().
mod.assn	the output of Macarron::findMacMod().
metadata_variable	name or index of metadata column identifying phenotypes/conditions to be used for evaluating AVA. Default: Column 1 of metadata dataframe. Note: metadata_variable must be consistent across distance matrix, ava, q-value and effect-size calculations.
anchor_annotation	name or index of column containing common names of the annotated metabolite. Default: Column 2 of annotation dataframe.

Value

mac.ava abundance versus anchor values of metabolic features

Examples

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)

biobakery/MACARRoN documentation built on July 1, 2024, 10:01 p.m.