| Popis: |
Large scale data resources such as the NCI’s Cancer Research Data Commons (CRDC) and the Genotype-Tissue Expression (GTEx) portal have the potential to simplify the analysis of cancer data by providing data that can be used as standards or controls. However, comparisons with data that is processed using different methodologies or even different versions of software, parameters and supporting datasets can lead to artefactual results. Reproducing the exact workflows from text-based standard operating procedures (SOPs) is problematic as the documentation can be incomplete or out of date, especially for complex workflows involving many executables and scripts. We extend our open-source Biodepot-workflow-builder (Bwb) platform to provide a dynamic solution that disseminates the computational protocols to process large-scale sequencing data developed by the National Cancer Institute (NCI) Genomic Data Commons (GDC). Specifically, we converted the GDC DNA sequencing (DNA-Seq) and the GDC mRNA sequencing (mRNA-Seq) SOPs into reproducible, self-installing, containerized, and interactive graphical workflows. Secure integration with protected-access CRDC data is achieved using the Data Commons Framework Services (DCFS) Gen3 protocol. These graphical workflows can be applied to reproducibly analyze datasets across other repositories and/or custom user data. Analyses can be performed on a local laptop, desktop, or cloud providers. With RNA-Seq datasets from the GDC and GTEx, we illustrate the importance of uniform analysis of control and treatment data for accurate inference of differentially expressed genes. Furthermore, we demonstrate that these best practices for analyzing RNA-seq data from different sources can be achieved using our accessible workflows. Most importantly, we demonstrate how our reproducible distribution of the methodology can transform the analyses of cancer genomic data by enabling researchers to leverage datasets across multiple repositories to enhance data interpretation. |
