Combat Normalization

ComBat Normalization is a statistical harmonization method that corrects batch effects in high-throughput genomic data by adjusting for non-biological variations across batches while preserving biological signals through an empirical Bayes framework.

8

Publications

619

Citations

34

Authors

20

Institutions

Publications per year

2017–2026

6

Variants

Combat

Authors

34

  1. CA
    Chloé‐Agathe Azencott

    Institut Curie, France

    2 publications · 195 citations

    2

    h-index

  2. CD
    Claire Duvallet

    Massachusetts Institute of Technology, United States

    2 publications · 197 citations

    2

    h-index

  3. AP
    Aryo Pradipta Gema

    University of Edinburgh, United Kingdom

    2 publications · 195 citations

    2

    h-index

  4. AN
    Akpéli Nordor

    Institut Curie, France

    2 publications · 195 citations

    2

    h-index

  5. AB
    Abdelkader Behdenna

    MRC University of Glasgow Centre for Virus Research, United Kingdom

    2 publications · 195 citations

    2

    h-index

1–5 of 34

Venues

  1. BMC Bioinformatics

    3 publications · 257 citations

    3

    h-index

  2. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 2 publications · 63 citations

    2

    h-index

  3. BMC Genomics

    1 publications · 35 citations

    1

    h-index

  4. PLoS Computational Biology

    1 publications · 181 citations

    1

    h-index

  5. BMC Medical Genomics

    1 publications · 83 citations

    1

    h-index

1–5