Identifying tumorigenic non-coding mutations through altered cis-regulation

Summary: Identification of non-coding mutations driving tumorigenesis requires alternative approaches to coding mutations. Enriched associations between mutated regulatory elements and altered cis-regulation in tumors are a promising approach to stratify candidate non-coding driver mutations. Here w...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Zhongshan Cheng, Michael Vermeulen, Micheal Rollins-Green, Tomas Babak, Brian DeVeale
Formato: article
Lenguaje:EN
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://doaj.org/article/6395de5f28e04b289848e10d87506912
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:Summary: Identification of non-coding mutations driving tumorigenesis requires alternative approaches to coding mutations. Enriched associations between mutated regulatory elements and altered cis-regulation in tumors are a promising approach to stratify candidate non-coding driver mutations. Here we provide a bioinformatics pipeline to mine data from the Cancer Genomic Commons (GDC) for such associations. The pipeline integrates RNA and whole-genome sequencing with genotyping data to reveal putative non-coding driver mutations by cancer type.For complete information on the generation and use of this protocol, please refer to Cheng et al. (2021).