Transcript Dropout Assessment

Transcript Dropout Assessment is a methodological procedure in single-cell RNA sequencing analysis that identifies and quantifies the failure of transcript detection due to technical limitations, distinguishing it from biological absence by evaluating the discrepancy between expected and observed transcript counts.

12

Publications

2.6K

Citations

39

Authors

31

Institutions

Publications per year

2017–2026

12

Authors

39

  1. FP
    Fanny Perraudeau

    University of California, Berkeley, United States

    2 publications · 879 citations

    2

    h-index

  2. QZ
    Qiming Zhang

    Peking University, China

    2 publications · 352 citations

    2

    h-index

  3. YH
    Yao He

    Peking University, China

    2 publications · 352 citations

    2

    h-index

  4. SD
    Sandrine Dudoit

    University of California, Berkeley, United States

    2 publications · 879 citations

    2

    h-index

  5. NK
    Naoko Koyano‐Nakagawa

    University of Minnesota, United States

    2 publications · 357 citations

    2

    h-index

1–5 of 39

Venues

  1. BMC Bioinformatics

    3 publications · 374 citations

    3

    h-index

  2. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 3 publications · 69 citations

    3

    h-index

  3. Nature Communications

    2 publications · 1.6K citations

    2

    h-index

  4. PLoS Computational Biology

    1 publications · 17 citations

    1

    h-index

  5. Genomics Proteomics & Bioinformatics

    1 publications · 336 citations

    1

    h-index

1–5