
Volatility Test on Principal Coordinates for Longitudinal Data
Source:R/generate_beta_pc_volatility_test_long.R
generate_beta_pc_volatility_test_long.RdTests association between PC coordinate volatility and group variable for longitudinal microbiome data.
Arguments
- data.obj
A MicrobiomeStat data object, which is a list containing at minimum the following components:
feature.tab: A matrix of feature abundances (taxa/genes as rows, samples as columns)meta.dat: A data frame of sample metadata (samples as rows)
Optional components include:
feature.ann: A matrix/data frame of feature annotations (e.g., taxonomy)tree: A phylogenetic tree object (class "phylo")feature.agg.list: Pre-aggregated feature tables by taxonomy
Data objects can be created using converters like
mStat_convert_phyloseq_to_data_objor importers likemStat_import_qiime2_as_data_obj.- dist.obj
A list of pre-calculated distance matrices. If NULL and distances are needed, they will be calculated automatically. List names should match dist.name (e.g., "BC" for Bray-Curtis). See
mStat_calculate_beta_diversity.- pc.obj
A list containing dimension reduction results from
mStat_calculate_PC. If NULL, PCoA is performed automatically.- pc.ind
Numeric vector specifying which PC axes to test. Default c(1, 2).
- subject.var
Character string specifying the column name in meta.dat that uniquely identifies each subject or sample unit. Required for longitudinal and paired designs to track repeated measurements.
- time.var
Character string specifying the column name in meta.dat containing the time variable. Required for longitudinal and paired analyses. Supports character/factor labels (e.g., "baseline", "week4") and numeric values. Some trend/volatility methods require numeric or coercible-to-numeric time values.
- group.var
Required. Character string specifying the grouping variable in metadata.
- adj.vars
Character vector specifying column names in meta.dat to be used as covariates for adjustment in statistical models. These variables will be included as fixed effects.
- dist.name
Character vector specifying which distance metrics to use. Options depend on available methods:
"BC": Bray-Curtis dissimilarity
"Jaccard": Jaccard distance
"UniFrac": Unweighted UniFrac (requires tree)
"GUniFrac": Generalized UniFrac (requires tree)
"WUniFrac": Weighted UniFrac (requires tree)
"JS": Jensen-Shannon divergence
- ...
Additional arguments passed to internal functions.