set_ANCOM: set_ANCOM

In mcalgaro93/benchdamic: Benchmark of differential abundance methods on microbiome data

set_ANCOM

Description

Set the parameters for ANCOM differential abundance detection method.

Usage

set_ANCOM(
  assay_name = "counts",
  pseudo_count = FALSE,
  fix_formula = NULL,
  adj_formula = NULL,
  rand_formula = NULL,
  lme_control = lme4::lmerControl(),
  contrast = NULL,
  alpha = 0.05,
  p_adj_method = "BH",
  struc_zero = FALSE,
  BC = TRUE,
  n_cl = 1,
  expand = TRUE
)

Arguments

assay_name	the name of the assay to extract from the TreeSummarizedExperiment object (default assayName = "counts"). Not used if the input object is a phyloseq.
pseudo_count	add 1 to all counts if TRUE (default pseudo_count = FALSE).
fix_formula	Used when BC = TRUE (ANCOM-BC2). The character string expresses how the microbial absolute abundances for each taxon depend on the fixed effects in metadata.
adj_formula	Used when BC = FALSE (ANCOM). The character string represents the formula for covariate adjustment. Default is NULL.
rand_formula	Optionally used when BC = TRUE or BC = FALSE. The character string expresses how the microbial absolute abundances for each taxon depend on the random effects in metadata. ANCOMB and ANCOM-BC2 follows the lmerTest package in formulating the random effects. See ?lmerTest::lmer for more details. Default is rand_formula = NULL.
lme_control	a list of control parameters for mixed model fitting. See ?lme4::lmerControl for details.
contrast	character vector with exactly, three elements: a string indicating the name of factor whose levels are the conditions to be compared, the name of the level of interest, and the name of the other level.
alpha	numeric. Level of significance. Default is 0.05.
p_adj_method	character. method to adjust p-values. Default is "holm". Options include "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none". See ?stats::p.adjust for more details.
struc_zero	logical. Whether to detect structural zeros based on group. Default is FALSE. See Details for a more comprehensive discussion on structural zeros.
BC	boolean for ANCOM method to use. If TRUE the bias correction (ANCOM-BC2) is computed (default BC = TRUE). When BC = FALSE computational time may increase and p-values are not computed.
n_cl	numeric. The number of nodes to be forked. For details, see ?parallel::makeCluster. Default is 1 (no parallel computing).
expand	logical, if TRUE create all combinations of input parameters (default expand = TRUE).

Value

A named list containing the set of parameters for DA_ANCOM method.

See Also

DA_ANCOM

Examples

# Set some basic combinations of parameters for ANCOM with bias correction
base_ANCOMBC <- set_ANCOM(pseudo_count = FALSE, fix_formula = "group", 
    contrast = c("group", "B", "A"), BC = TRUE, expand = FALSE)
many_ANCOMs <- set_ANCOM(pseudo_count = c(TRUE, FALSE), 
    fix_formula = "group", contrast = c("group", "B", "A"), 
    struc_zero = c(TRUE, FALSE), BC = c(TRUE, FALSE))

mcalgaro93/benchdamic documentation built on Nov. 23, 2024, 5:06 p.m.