Cargando…
A framework to score the effects of structural variants in health and disease
Although technological advances improved the identification of structural variants (SVs) in the human genome, their interpretation remains challenging. Several methods utilize individual mechanistic principles like the deletion of coding sequence or 3D genome architecture disruptions. However, a com...
Autores principales: | Kleinert, Philip, Kircher, Martin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8997355/ https://www.ncbi.nlm.nih.gov/pubmed/35197310 http://dx.doi.org/10.1101/gr.275995.121 |
Ejemplares similares
-
LUMPY: a probabilistic framework for structural variant discovery
por: Layer, Ryan M, et al.
Publicado: (2014) -
SVFX: a machine learning framework to quantify the pathogenicity of structural variants
por: Kumar, Sushant, et al.
Publicado: (2020) -
SubcloneSeeker: a computational framework for reconstructing tumor clone structure for cancer variant interpretation and prioritization
por: Qiao, Yi, et al.
Publicado: (2014) -
A framework for exhaustively mapping functional missense variants
por: Weile, Jochen, et al.
Publicado: (2017) -
A general framework for identifying oligogenic combinations of rare variants in complex disorders
por: Pounraja, Vijay Kumar, et al.
Publicado: (2022)