combat_harm: ComBatFamily Harmonization

In ComBatFamQC: Comprehensive Batch Effect Diagnostics and Harmonization

ComBatFamily Harmonization

Description

Conduct harmonization using four types of methods: 1) Original ComBat, 2) Longitudinal ComBat, 3) ComBat-GAM, and 4) CovBat.

Usage

combat_harm(
  eb_check = FALSE,
  result = NULL,
  features = NULL,
  batch = NULL,
  covariates = NULL,
  df = NULL,
  type = "lm",
  random = NULL,
  smooth = NULL,
  interaction = NULL,
  smooth_int_type = NULL,
  family = "comfam",
  eb = TRUE,
  ref.batch = NULL,
  predict = FALSE,
  object = NULL,
  reference = NULL,
  out_ref_include = TRUE,
  ...
)

Arguments

eb_check	A boolean variable indicating whether the user wants to run the EB assumption test before harmonization.
result	A list derived from visual_prep() that contains dataset and batch effect diagnostic information for Shiny visualization. Can be skipped if features, batch, covariates and df are provided.
features	The name of the features to be harmonized. This can be skipped if result is provided.
batch	The name of the batch variable. Can be skipped if result is provided.
covariates	The names of covariates supplied to model. This can be be skipped if result is provided.
df	Dataset to be harmonized. This can be be skipped if result is provided.
type	The name of a regression model to be used: "lmer", "lm", "gam".
random	The variable name of a random effect in linear mixed effect model.
smooth	The name of the covariates that require a smooth function.
interaction	Expression of interaction terms supplied to model (eg: "age,diagnosis").
smooth_int_type	A vector that indicates the types of interaction in gam models. By default, smooth_int_type is set to be NULL, "linear" represents linear interaction terms. "categorical-continuous", "factor-smooth" both represent categorical-continuous interactions ("factor-smooth" includes categorical variable as part of the smooth), "tensor" represents interactions with different scales, and "smooth-smooth" represents interaction between smoothed variables.
family	The type of combat family to use, comfam or covfam.
eb	If TRUE, uses ComBat model with empirical Bayes for mean and variance harmonization
ref.batch	The name of the reference batch.
predict	A boolean variable indicating whether to run ComBat from scratch or apply existing model to new dataset (currently only work for original ComBat and ComBat-GAM).
object	Existing ComBat model.
reference	Dataset to be considered as the reference group.
out_ref_include	A boolean variable indicating whether the reference data should be included in the harmonized data output.
...	Additional arguments to comfam or covfam models.

Value

If the eb_check is set to be FALSE, then combat_harm returns a list containing the following components:

com_family	ComBat family to be considered: comfam, covfam
harmonized_df	Harmonized dataset
combat.object	Saved ComBat model and relevant information, such as the batch variable name and whether the EB method is used

If eb_check is set to be TRUE, then combat_harm will return a dataframe with the EB assumption test result.

Examples

combat_harm(features = colnames(adni)[43:53], batch = "manufac",
covariates = c("AGE", "SEX", "DIAGNOSIS"), df = head(adni,100), type = "lm")

ComBatFamQC documentation built on April 4, 2025, 12:24 a.m.