Transparent Incremental Updates for Genomics Data Analysis Pipelines
A large up-to-date compendium of integrated genomic data is often required for biological data analysis. The compendium can be tens of terabytes in size, and must often be frequently updated with new experimental or meta-data. Manual compendium update is cumbersome, requires a lot of unnecessary computation, and it may result in errors or inconsistencies in the compendium. We propose a transparent file based approach for adding incremental update ca-pabilities to unmodified genomics data analysis tools and pipeline workflow managers. This approach is implemented in the GeStore system. We evaluate GeStore using a real world genomics compendium. Our results show that it is easy to add incremental updates to genomics data processing pipelines, and that incremental updates can reduce the computation time such that it becomes prac-tical to maintain large-scale up-to-date genomics compendia on small clusters.
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-54420-0_31
ForlagSpringer Berlin Heidelberg
SerieEuro-Par 2013: Parallel Processing Workshops, Lecture Notes in Computer Science, Vol. 8374, 2014, pp 311-320
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