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 data, although suitable big data strategies still address mainly primary and secondary analysis. Hence, there is a pressing need for algorithms specifically designed to explore big omics datasets, capable of ensuring scalability and interoperability, possibly relying on high-performance computing infrastructures.

Results

We propose RGMQL, a R/Bioconductor package conceived to provide a set of specialized functions to extract, combine, process and compare omics datasets and their metadata from

SUBMITTER: Pallotta S 

PROVIDER: S-EPMC8991469 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature