Batch Effect Detection

Batch Effect Detection is a methodological approach in single-cell quality control that identifies systematic, non-biological variations introduced during experimental processing steps, distinguished by its specific focus on detecting technical artifacts that confound biological signal across batches.

93

Publications

6.4K

Citations

490

Authors

241

Institutions

Publications per year

2017–2026

71

Authors

490

  1. AL
    Adam Lerer

    Meta (Israel), Israel

    3 publications · 92 citations

    3

    h-index

  2. HC
    Huidong Chen

    Harvard University, United States

    3 publications · 92 citations

    3

    h-index

  3. WW
    Wilson Wen Bin Goh

    Nanyang Technological University, Singapore

    3 publications · 257 citations

    3

    h-index

  4. MV
    Michael Vinyard

    Harvard University, United States

    3 publications · 92 citations

    3

    h-index

  5. XL
    Xiangjie Li

    Northwestern Polytechnical University, China

    3 publications · 169 citations

    3

    h-index

1–5 of 490

Venues

  1. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 9 publications · 206 citations

    9

    h-index

  2. Bioinformatics

    9 publications · 530 citations

    9

    h-index

  3. BMC Bioinformatics

    7 publications · 562 citations

    7

    h-index

  4. Nature Communications

    5 publications · 293 citations

    5

    h-index

  5. Genome biology

    4 publications · 320 citations

    4

    h-index

1–5