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 heterogeneously processed datasets. Available software packages are suitable for analyzing experimental files from such datasets one by one, but do not scale to thousands of experiments. Moreover, they lack proper support for metadata manipulation.

Results

We present PyGMQL, a novel software for the manipulation of region-based genomic files and their relative metadata, built on top of the GMQL genomic big data management system. PyGMQL provides a set of expressive functions for the manipulation of r

SUBMITTER: Nanni L 

PROVIDER: S-EPMC6842186 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature