Transcriptome Quality Control

Transcriptome Quality Control is a methodological framework that systematically assesses and ensures the accuracy, completeness, and reliability of transcriptomic data by identifying and mitigating technical artifacts, sequencing errors, and biases introduced during sample preparation, sequencing, and initial data processing.

84

Publications

14.3K

Citations

740

Authors

326

Institutions

Publications per year

2017–2026

34

Authors

740

  1. DT
    Danielle Thierry‐Mieg

    National Center for Biotechnology Information, United States

    4 publications · 3.2K citations

    4

    h-index

  2. JT
    Jean Thierry‐Mieg

    National Center for Biotechnology Information, United States

    4 publications · 3.2K citations

    4

    h-index

  3. WT
    Weida Tong

    National Center for Toxicological Research, United States

    3 publications · 3.1K citations

    3

    h-index

  4. LW
    Liguo Wang

    Mayo Clinic, United States

    3 publications · 3.4K citations

    3

    h-index

  5. AS
    Andreas Scherer

    Institute for Molecular Medicine Finland, Finland

    3 publications · 1K citations

    3

    h-index

1–5 of 740

Venues

  1. PLoS ONE

    6 publications · 254 citations

    6

    h-index

  2. Bioinformatics

    5 publications · 4.5K citations

    5

    h-index

  3. Nature Biotechnology

    5 publications · 4.2K citations

    5

    h-index

  4. BMC Bioinformatics

    5 publications · 1.3K citations

    5

    h-index

  5. BMC Genomics

    4 publications · 555 citations

    4

    h-index

1–5