Title | Hadoop and PySpark for reproducibility and scalability of genomic sequencing studies. |
Publication Type | Journal Article |
Year of Publication | 2020 |
Authors | Wheeler NR, Benchek P, Kunkle BW, Hamilton-Nelson KL, Warfe M, Fondran JR, Haines JL, Bush WS |
Journal | Pac Symp Biocomput |
Volume | 25 |
Pagination | 523-534 |
Date Published | 2020 |
ISSN | 2335-6936 |
Keywords | Base Sequence, Chromosome Mapping, Computational Biology, Diagnostic Tests, Routine, Genomics, High-Throughput Nucleotide Sequencing, Humans, Reproducibility of Results, Sequence Analysis, DNA, Software, Workflow |
Abstract | Modern genomic studies are rapidly growing in scale, and the analytical approaches used to analyze genomic data are increasing in complexity. Genomic data management poses logistic and computational challenges, and analyses are increasingly reliant on genomic annotation resources that create their own data management and versioning issues. As a result, genomic datasets are increasingly handled in ways that limit the rigor and reproducibility of many analyses. In this work, we examine the use of the Spark infrastructure for the management, access, and analysis of genomic data in comparison to traditional genomic workflows on typical cluster environments. We validate the framework by reproducing previously published results from the Alzheimer's Disease Sequencing Project. Using the framework and analyses designed using Jupyter notebooks, Spark provides improved workflows, reduces user-driven data partitioning, and enhances the portability and reproducibility of distributed analyses required for large-scale genomic studies. |
Pubmed Link | https://www.ncbi.nlm.nih.gov/pubmed/31797624?dopt=Abstract |
page_expo | Internal |
Alternate Journal | Pac Symp Biocomput |
PubMed ID | 31797624 |
PubMed Central ID | PMC6956992 |
Grant List | RF1 AG054074 / AG / NIA NIH HHS / United States U01 AG052410 / AG / NIA NIH HHS / United States U01 AG058654 / AG / NIA NIH HHS / United States U54 AG052427 / AG / NIA NIH HHS / United States |
Theme by Danetsoft and Danang Probo Sayekti inspired by Maksimer