ArticleBioinformatics advances2022
reComBat: batch-effect removal in large-scale multi-source gene-expression data integration.
Article in Bioinformatics advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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Who cites it
18 citing papers in PubMed.
- Single-cell map of the healthy human immune system across the lifespan reveals unique infant immune signatures.Nature communications · 2026Article
- Batch correction for large-scale mass spectrometry imaging experiments.Bioinformatics (Oxford, England) · 2026Article
- A novel batch effect correction framework for robust integration of high-variance data via a global-information virtual reference batch.Frontiers in microbiology · 2026Article
- Age-related evolution of human gingiva towards a fibrotic-like connective phenotype.Scientific reports · 2025Article
- Article
- Identification and validation of anoikis-related differentially expressed genes in nasopharyngeal carcinoma.Translational cancer research · 2025Article
- Harnessing Multi-Omics and Predictive Modeling for Climate-Resilient Crop Breeding: From Genomes to Fields.Genes · 2025Review
- A lipid atlas of the human kidney.Science advances · 2025Article
- Single-cell morphology encodes functional subtypes of senescence in aging human dermal fibroblasts.Science advances · 2025Article
- iComBat: An incremental framework for batch effect correction in DNA methylation array data.Computational and structural biotechnology journal · 2025Article
- A robust transfer learning approach for high-dimensional linear regression to support integration of multi-source gene expression data.PLoS computational biology · 2025Article
- Enhanced metagenomic strategies for elucidating the complexities of gut microbiota: a review.Frontiers in microbiology · 2025Review
- Epistemic uncertainty challenges aging clock reliability in predicting rejuvenation effects.Aging cell · 2024Article
- Assessing and mitigating batch effects in large-scale omics studies.Genome biology · 2024Review
- Thinking points for effective batch correction on biomedical data.Briefings in bioinformatics · 2024Article
- Identification of hub genes and their correlation with immune infiltrating cells in membranous nephropathy: an integrated bioinformatics analysis.European journal of medical research · 2023Article
- Single cell dynamics of tumor specificity vs bystander activity in CD8Cell discovery · 2023Article
- Dual adversarial deconfounding autoencoder for joint batch-effects removal from multi-center and multi-scanner radiomics data.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: With the steadily increasing abundance of omics data produced all over the world under vastly different experimental conditions residing in public databases, a crucial step in many data-driven bioinformatics applications is that of data integration. The challenge of batch-effect removal for entire databases lies in the large number of batches and biological variation, which can result in design matrix singularity. This problem can currently not be solved satisfactorily by any common batch-correction algorithm. Results: We present Availability and implementation: The code is available at https://github.com/BorgwardtLab/reComBat, all data and evaluation code can be found at https://github.com/BorgwardtLab/batchCorrectionPublicData. Supplementary information: Supplementary data are available at
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.