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Test Beta Diversity Change Between Time Points

Source: R/generate_beta_change_test_pair.R
generate_beta_change_test_pair.Rd

Tests within-subject beta diversity changes between two time points using linear models. Supports group comparisons and covariate adjustment.

Usage

generate_beta_change_test_pair(
  data.obj,
  dist.obj = NULL,
  subject.var,
  time.var = NULL,
  group.var,
  adj.vars = NULL,
  change.base = NULL,
  dist.name = c("BC", "Jaccard")
)

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_obj or importers like mStat_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.

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

Character string specifying the column name in meta.dat containing the grouping variable (e.g., treatment, condition, phenotype). Used for between-group comparisons.

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.

change.base

Character or numeric specifying the baseline time point. If NULL, uses the first time point.

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

Value

A named list containing linear modeling results for each beta diversity metric. Each list element corresponds to one of the distance metrics specified in dist.name. It contains a coefficient table from fitting a linear model with the beta diversity change as response and the group_var and adj_vars as predictors. If group_var has multiple levels, ANOVA results are also included after the coefficients. Column names include: Term, Estimate, Std.Error, Statistic, P.Value

Examples

if (FALSE) { # \dontrun{

# Load packages
library(vegan)

# Load data
data(peerj32.obj)
generate_beta_change_test_pair(
  data.obj = peerj32.obj,
  dist.obj = NULL,
  subject.var = "subject",
  time.var = "time",
  group.var = "group",
  adj.vars = NULL,
  change.base = "1",
  dist.name = c('BC', 'Jaccard')
)
generate_beta_change_test_pair(
  data.obj = peerj32.obj,
  dist.obj = NULL,
  subject.var = "subject",
  time.var = "time",
  group.var = "group",
  adj.vars = "sex",
  change.base = "1",
  dist.name = c('BC', 'Jaccard')
)

data("subset_pairs.obj")
generate_beta_change_test_pair(
  data.obj = subset_pairs.obj,
  dist.obj = NULL,
  subject.var = "MouseID",
  time.var = "Antibiotic",
  group.var = "Sex",
  adj.vars = NULL,
  change.base = "Baseline",
  dist.name = c('BC', 'Jaccard')
)
} # }