Cargando…
A Bayesian model for unsupervised detection of RNA splicing based subtypes in cancers
Identification of cancer sub-types is a pivotal step for developing personalized treatment. Specifically, sub-typing based on changes in RNA splicing has been motivated by several recent studies. We thus develop CHESSBOARD, an unsupervised algorithm tailored for RNA splicing data that captures “tile...
Autores principales: | Wang, David, Quesnel-Vallieres, Mathieu, Jewell, San, Elzubeir, Moein, Lynch, Kristen, Thomas-Tikhonenko, Andrei, Barash, Yoseph |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9813260/ https://www.ncbi.nlm.nih.gov/pubmed/36599821 http://dx.doi.org/10.1038/s41467-022-35369-0 |
Ejemplares similares
-
Identifying common transcriptome signatures of cancer by interpreting deep learning models
por: Jha, Anupama, et al.
Publicado: (2022) -
MOCCASIN: a method for correcting for known and unknown confounders in RNA splicing analysis
por: Slaff, Barry, et al.
Publicado: (2021) -
Rapid and Scalable Profiling of Nascent RNA with fastGRO
por: Barbieri, Elisa, et al.
Publicado: (2020) -
Meta-analysis of transcriptomic variation in T-cell populations reveals both variable and consistent signatures of gene expression and splicing
por: Radens, Caleb M., et al.
Publicado: (2020) -
High-throughput mutagenesis identifies mutations and RNA-binding proteins controlling CD19 splicing and CART-19 therapy resistance
por: Cortés-López, Mariela, et al.
Publicado: (2022)