Sample Cross-contamination Detection

Sample Cross-Contamination Detection is a metagenomic data quality control method that identifies the presence of foreign genetic material in a sample by distinguishing contaminant sequences from target organism sequences based on taxonomic inconsistency, sequence composition, or statistical deviation from expected microbial community profiles.

36

Publications

3.6K

Citations

238

Authors

109

Institutions

Publications per year

2017–2026

15

Authors

238

  1. JS
    John S. Vogel

    Lawrence Livermore National Laboratory, United States

    3 publications · 417 citations

    3

    h-index

  2. YJ
    Yongfeng Jia

    Inner Mongolia Medical University, China

    1 publications · 14 citations

    1

    h-index

  3. XE
    Xavier Estivill

    Centre for Genomic Regulation, Spain

    1 publications · 96 citations

    1

    h-index

  4. JP
    Jan Pawłowski

    University of Geneva, Switzerland

    1 publications · 346 citations

    1

    h-index

  5. KB
    Khalid Belkhir

    Université de Montpellier, France

    1 publications · 113 citations

    1

    h-index

1–5 of 238

Venues

  1. Analytical Chemistry

    4 publications · 353 citations

    4

    h-index

  2. Bioinformatics

    3 publications · 479 citations

    3

    h-index

  3. Clinical Chemistry

    2 publications · 149 citations

    2

    h-index

  4. Nucleic Acids Research

    2 publications · 387 citations

    2

    h-index

  5. Radiocarbon

    2 publications · 257 citations

    2

    h-index

1–5