Rank Normalization

Rank Normalization is a data preprocessing method that transforms omics measurements by replacing raw values with their rank-ordered positions within samples, followed by normalization to a standard distribution, thereby reducing technical variability and improving comparability across datasets while preserving relative expression patterns.

58

Publications

13.1K

Citations

163

Authors

85

Institutions

Publications per year

2017–2026

13

Variants

Rank-based Normalization

Authors

163

  1. RF
    Robert F. Woolson

    University of Iowa, United States

    2 publications · 24 citations

    2

    h-index

  2. MF
    Milton Friedman

    Hoover Institution, United States

    2 publications · 4K citations

    2

    h-index

  3. TW
    Thomas W. O’Gorman

    University of Iowa, United States

    2 publications · 24 citations

    2

    h-index

  4. MB
    Milica Bulajić

    University of Belgrade, Serbia

    1 publications · 53 citations

    1

    h-index

  5. SC
    Stephen C. Hora

    University of Hawaii at Hilo, United States

    1 publications · 45 citations

    1

    h-index

1–5 of 163

Venues

  1. Journal of the American Statistical Association

    5 publications · 9.1K citations

    5

    h-index

  2. BMC Bioinformatics

    3 publications · 263 citations

    3

    h-index

  3. Scientometrics

    2 publications · 71 citations

    2

    h-index

  4. Genomics

    2 publications · 162 citations

    2

    h-index

  5. Statistics in Medicine

    3 publications · 45 citations

    2

    h-index

1–5