RGMQL: scalable and interoperable computing of heterogeneous omics big data and metadata in R/Bioconductor

RGMQL: scalable and interoperable computing of heterogeneous omics big data and metadata in R/Bioconductor

Abstract Background Heterogeneous omics data, increasingly collected through high-throughput technologies, can contain hidden answers to very important and still unsolved biomedical questions. Their integration and processing are crucial mostly for tertiary analysis of Next Generation Sequencing dat...

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Bibliographic Details
Main Authors: Simone Pallotta, Silvia Cascianelli, Marco Masseroli
Format: Article
Language:English
Published: BMC 2022-04-01
Series:BMC Bioinformatics
Subjects:
Heterogeneous omics big data
Data scalability
Distribution transparency
Tertiary data analysis
Online Access:https://doi.org/10.1186/s12859-022-04648-4

Internet

https://doi.org/10.1186/s12859-022-04648-4

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