Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Type VI secretion system-mediated bacterial antagonism in the classroom.

Access microbiology·2026

Same author

Opposing range-dependent interactions create complex spatial patterns of antibiotic tolerance in multispecies biofilms.

Proceedings of the National Academy of Sciences of the United States of America·2026

Same author

Large Language Model-Based Classification of Case Report Abstracts: A Pilot Study on Interactions Between Radiotherapy and Systemic Therapies.

JCO clinical cancer informatics·2026

Same author

Advancing mold identification in the routine laboratory, performance of smartphone-based imaging and a newly developed convolutional neural network.

Microbiology spectrum·2025

Same author

Mechanisms of Pseudomonas aeruginosa resistance to type VI secretion system attacks.

Nature communications·2025

Same author

Circulation of polyclonal OXA-244-producing <i>Escherichia coli</i> lineages in Jerusalem, Israel.

JAC-antimicrobial resistance·2025

Same journal

Region-aware bridge modeling enables interpretable mesoscale representation of spatial transcriptomic tissue sections.

Bioinformatics advances·2026

Same journal

Microbiome differential abundance methodologies to detect relevant taxa associated with chemotherapy toxicity rate in colorectal cancer.

Bioinformatics advances·2026

Same journal

maldipickr dereplicates microbial MALDI-TOF spectra to facilitate multiplexed isolation.

Bioinformatics advances·2026

Same journal

RAM-MSA: an anytime memory-bounded method for exact multiple sequence alignment using path finding.

Bioinformatics advances·2026

Same journal

Interpretable machine learning for low-sample multi-omics: a case study of ferret vaccine response.

Bioinformatics advances·2026

Same journal

DeepTaxa: a hybrid CNN-BERT framework for 16S rRNA taxonomic classification.

Bioinformatics advances·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 29, 2026

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

reComBat: batch-effect removal in large-scale multi-source gene-expression data integration.

Michael F Adamer^1,2, Sarah C Brüningk^1,2, Alejandro Tejada-Arranz³

¹Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland.

Bioinformatics Advances

|January 26, 2023

Summary

This summary is machine-generated.

Batch-effect removal in large omics databases is challenging. We introduce reComBat, a regularized empirical Bayes method that successfully harmonizes public gene-expression data while preserving biological variation.

More Related Videos

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

Related Experiment Videos

Last Updated: Jun 29, 2026

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

Published on: March 12, 2021

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

Area of Science:

Bioinformatics
Genomics
Computational Biology

Background:

Increasing volumes of omics data from diverse sources present integration challenges.
Batch effects, arising from varied experimental conditions, complicate data harmonization.
Existing batch-correction algorithms struggle with large-scale databases and complex biological variation.

Purpose of the Study:

To develop a robust method for batch-effect removal in large-scale omics databases.
To address the limitations of current algorithms in handling numerous batches and biological variability.
To enable effective data integration for comprehensive bioinformatics analyses.

Main Methods:

Introduced reComBat, a regularized empirical Bayes approach.
Benchmarked reComBat against popular methods using public gene-expression data (microarray and bulkRNAseq) of *Pseudomonas aeruginosa*.
Evaluated batch-effect mitigation and retention of biological variation.

Main Results:

reComBat successfully mitigated batch effects in public gene-expression datasets.
Biologically meaningful gene-expression variation was retained after harmonization.
The method demonstrated superior performance in harmonizing large-scale, heterogeneous omics data.

Conclusions:

reComBat effectively addresses the challenge of batch-effect removal in large omics databases.
This method facilitates data-driven analysis of complex biological processes across multiple studies.
reComBat fills a critical gap in bioinformatics tools for omics data integration.