PyGMQL: scalable data extraction and analysis for heterogeneous genomic datasets

PyGMQL: scalable data extraction and analysis for heterogeneous genomic datasets

Abstract 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 heterogeneo...

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Bibliographic Details
Main Authors: Luca Nanni, Pietro Pinoli, Arif Canakoglu, Stefano Ceri
Format: Article
Language:English
Published: BMC 2019-11-01
Series:BMC Bioinformatics
Subjects:
Genomic data
Data scalability
Tertiary data analysis
Distribution transparency
Python
Online Access:http://link.springer.com/article/10.1186/s12859-019-3159-9

Internet

http://link.springer.com/article/10.1186/s12859-019-3159-9

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