Motivation: 0.1The Genomic Data Commons is a powerful resource which facilitates the exploration of molecular alterations across various diseases. However, utilizing this resource for meta-analysis requires many different tools to query, download, organize, and analyze the data. In order to facilitate a more rapid, simple means of analyzing DNA methylation and RNA sequencing datasets from the GDC we developed autogdc, a python package that integrates data curation and preprocessing with meta-analysis functionality into one simplified bioinformatic pipeline.
Availability and implementation: 0.2The autogdc python package is available under the GPLv3 license at along with several examples of typical use-case scenarios in the form of a jupyter notebook. The data is all originally provided by the GDC, and is therefore available under the NIH Genomic Data Sharing (GDS) and NCI GDS policies.
Keywords: Bioinformatics; Cancer; Data analysis; Database; Epigenetics; Gene Expression; Genomic Data Commons.