PyGMQL: scalable data extraction and analysis for heterogeneous genomic datasets

BACKGROUND: With the growth of available sequenced datasets, analysis of heterogeneous processed data can answer increasingly relevant biological and clinical questions. Scientists are challenged in performing efficient and reproducible data extraction and analysis pipelines over heterogeneously pro...

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Detalles Bibliográficos
Autores principales: Nanni, Luca, Pinoli, Pietro, Canakoglu, Arif, Ceri, Stefano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Software
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6842186/
https://www.ncbi.nlm.nih.gov/pubmed/31703553
http://dx.doi.org/10.1186/s12859-019-3159-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6842186/
https://www.ncbi.nlm.nih.gov/pubmed/31703553
http://dx.doi.org/10.1186/s12859-019-3159-9

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