Tutorials

Typical Workflow

The ComBatFamQC workflow guides users from raw multi-site data to harmonized, analysis-ready results. You can run the full workflow using the R Shiny app or the command-line interface.

1. Data Preparation

Start with your unharmonized dataset that includes:

  • A feature matrix (e.g., cortical thickness, volume, or connectivity)
  • A metadata file containing covariates such as site, age, sex, and diagnosis

2. Batch Effect Diagnostics

Detect and measure site-related variation using interactive plots and statistical tests, including:

  • Interactive Plots: Residual Box Plots, Exploratory Density Plots, PCA/t-SNE Plots
  • Statistical Tests: ANOVA, Kruskal-Wallis, Levene’s, Bartlett’s tests

These diagnostics help determine whether harmonization is required and which method to apply.

3. Harmonization and Post-Analysis

Apply one of four harmonization methods (ComBat, Longitudinal ComBat, ComBat-GAM, or CovBat) to remove site effects while preserving biological variability. After harmonization, reassess batch effects, explore age trends, and generate residual datasets for downstream analysis.

The interactive workflow can be found below:

Click a node above to display a related figure here, or click an edge to see its explanation.

Tutorial Videos


Interactive Batch Effect Diagnostic

Data Overview

Figure 1: ComBatFamQC: Data Overview
This video introduces the ComBatFamQC interface and data structure, showing how input data are organized and prepared for harmonization.

Summary

Figure 2: ComBatFamQC: Summary
An overview of key summary statistics and visual outputs generated after harmonization, illustrating how ComBatFamQC evaluates data consistency.

Residual Plot

Figure 3: ComBatFamQC: Residual Plot
This tutorial explains how to interpret residual plots to assess whether batch effects remain after harmonization.

Diagnosis of Global Batch Effect

Figure 4: ComBatFamQC: Diagnosis of Global Batch Effect
Learn how to identify and visualize overall batch effects across datasets, helping ensure harmonization quality at a global level.

Diagnosis of Individual Batch Effect

Figure 5: ComBatFamQC: Diagnosis of Individual Batch Effect
This video focuses on assessing individual batch-level differences and detecting potential sources of variation after correction.

Interactive Harmonization

Figure 6: ComBatFamQC: Interactive Harmonization
Explore how to use the interactive ComBatFamQC interface to fine-tune harmonization parameters and visualize real-time effects.

Post-harmonization Analysis


Interactive Life Span Age Trend

Figure 7: Brain ROI Age Trend Visualization
This tutorial demonstrates how to visualize age-related changes across brain regions, highlighting lifespan trends using interactive plots.