Read Depth Analysis

Read Depth Analysis is a computational method in genomics that quantifies variations in DNA copy number by measuring the relative depth of sequencing reads aligned to a reference genome, distinguishing itself from other structural variation detection approaches through its reliance on the statistical distribution of read coverage to infer duplications or deletions.

167

Publications

15.9K

Citations

1.4K

Authors

501

Institutions

Publications per year

2017–2026

78

Authors

1.4K

  1. JD
    John D. Storey

    Princeton University, United States

    5 publications · 192 citations

    5

    h-index

  2. DG
    David G. Robinson

    Princeton University, United States

    5 publications · 192 citations

    5

    h-index

  3. VP
    Vincent Plagnol

    University College London, United Kingdom

    4 publications · 1.5K citations

    4

    h-index

  4. LC
    Lachlan Coin

    Imperial College London, United Kingdom

    4 publications · 82 citations

    4

    h-index

  5. FJ
    Francisco J. Pardo-Palacios

    University of Florida, United States

    3 publications · 290 citations

    3

    h-index

1–5 of 1.4K

Venues

  1. BMC Genomics

    17 publications · 2.1K citations

    15

    h-index

  2. PLoS ONE

    10 publications · 1.1K citations

    10

    h-index

  3. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 9 publications · 165 citations

    9

    h-index

  4. Frontiers in Genetics

    7 publications · 212 citations

    7

    h-index

  5. Bioinformatics

    7 publications · 1K citations

    7

    h-index

1–5