Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration
Integrated analyses of multiple large-scale screenings can be complicated by batch effects and technical artefacts. McFarland et al. introduce DEMETER2, a hierarchical model coupled with model-based normalization, which allows the assessment of differential dependencies across genes and cell lines.
Enregistré dans:
Auteurs principaux: | James M. McFarland, Zandra V. Ho, Guillaume Kugener, Joshua M. Dempster, Phillip G. Montgomery, Jordan G. Bryan, John M. Krill-Burger, Thomas M. Green, Francisca Vazquez, Jesse S. Boehm, Todd R. Golub, William C. Hahn, David E. Root, Aviad Tsherniak |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2018
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/d0eb361d0bb14b90ba18bfe3b6bb1fd5 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Global computational alignment of tumor and cell line transcriptional profiles
par: Allison Warren, et autres
Publié: (2021) -
Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets
par: Joshua M. Dempster, et autres
Publié: (2019) -
Integrated cross-study datasets of genetic dependencies in cancer
par: Clare Pacini, et autres
Publié: (2021) -
Complementary information derived from CRISPR Cas9 mediated gene deletion and suppression
par: Joseph Rosenbluh, et autres
Publié: (2017) -
RNAi Crop Protection Advances
par: Alejandro Hernández-Soto, et autres
Publié: (2021)