Reference-free Variant Analysis

Reference-Free Variant Analysis is a computational approach in metagenomic variant analysis that identifies genetic variations without relying on a reference genome, distinguishing itself from reference-based methods by enabling variant discovery through direct comparison of sequencing reads to assembled contigs or de novo assembly graphs.

12

Publications

2.4K

Citations

92

Authors

42

Institutions

Publications per year

2017–2026

8

Authors

92

  1. PP
    Pierre Peterlongo

    Institut de Recherche en Informatique et Systèmes Aléatoires, France

    2 publications · 135 citations

    2

    h-index

  2. MC
    Michael C. Schatz

    Johns Hopkins University, United States

    2 publications · 2.1K citations

    2

    h-index

  3. MN
    Maria Nattestad

    Johns Hopkins University, United States

    2 publications · 2.1K citations

    2

    h-index

  4. JG
    James Gurtowski

    Cold Spring Harbor Laboratory, United States

    2 publications · 2.1K citations

    2

    h-index

  5. FJ
    Fritz J. Sedlazeck

    Baylor College of Medicine, United States

    2 publications · 2.1K citations

    2

    h-index

1–5 of 92

Venues

  1. Molecular Ecology Resources

    3 publications · 65 citations

    3

    h-index

  2. Nucleic Acids Research

    2 publications · 139 citations

    2

    h-index

  3. Bioinformatics

    2 publications · 2K citations

    2

    h-index

  4. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 2 publications · 152 citations

    2

    h-index

  5. Cell

    1 publications · 20 citations

    1

    h-index

1–5