Harmonizing and integrating the NCI Genomic Data Commons through accessible, interactive, and cloud-enabled workflows

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Cancer data repositories like the National Cancer Institute (NCI) Genomic Data Commons (GDC) offer valuable datasets for comparative analyses.
• Reproducibly processing user data to match GDC standards is challenging due to text-based Standard Operating Procedures (SOPs) that often lag behind code revisions.

Purpose of the Study:

• To enhance the utility of the GDC by converting existing SOPs into an accessible and executable format.
• To enable reproducible processing of user data and harmonization of datasets across repositories.

Main Methods:

• Converted GDC DNA sequencing (DNA-Seq) and mRNA sequencing (mRNA-Seq) SOPs into reproducible, self-installing, containerized, and interactive graphical workflows.
• Harmonized raw RNA-Seq datasets from GDC and Genotype-Tissue Expression (GTEx) using the developed graphical workflows.

Main Results:

• Developed and disseminated open-source graphical workflows for GDC DNA-Seq and mRNA-Seq pipelines.
• Demonstrated the importance of uniform data processing for accurate differential gene expression analysis by harmonizing datasets processed with different methodologies.

Conclusions:

• The developed graphical workflows significantly increase the utility of the GDC by enabling researchers to uniformly process custom and existing datasets.
• This approach of making analytical methodologies as accessible as the data can be applied to other repositories to improve scientific research impact.