Quantifying deleterious effects of regulatory variants

The majority of genome-wide association study (GWAS) risk variants reside in non-coding DNA sequences. Understanding how these sequence modifications lead to transcriptional alterations and cell-to-cell variability can help unraveling genotype–phenotype relationships. Here, we describe a computation...

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Detalles Bibliográficos
Autores principales: Li, Shan, Alvarez, Roberto Vera, Sharan, Roded, Landsman, David, Ovcharenko, Ivan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Computational Biology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5389506/
https://www.ncbi.nlm.nih.gov/pubmed/27980060
http://dx.doi.org/10.1093/nar/gkw1263

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5389506/
https://www.ncbi.nlm.nih.gov/pubmed/27980060
http://dx.doi.org/10.1093/nar/gkw1263

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