Latest revision as of 17:16, 21 January 2021

Abstract

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-54420-0_31 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.

Original document

The different versions of the original document can be found in:

• https://hdl.handle.net/10037/6902

• https://hdl.handle.net/10037/7563

• https://munin.uit.no/bitstream/10037/7563/1/article.pdf

• http://link.springer.com/content/pdf/10.1007/978-3-642-54420-0_31,

http://dx.doi.org/10.1007/978-3-642-54420-0_31 under the license http://www.springer.com/tdm

• https://link.springer.com/chapter/10.1007/978-3-642-54420-0_31,

https://core.ac.uk/display/43615833,

https://dblp.uni-trier.de/db/conf/europar/europar2013w.html#PedersenWB13,

https://www.scipedia.com/public/Pedersen_et_al_2014a,

https://munin.uit.no/handle/10037/7563,

https://munin.uit.no/bitstream/handle/10037/7563/article.pdf?sequence=1&isAllowed=y,

https://munin.uit.no/bitstream/10037/7563/1/article.pdf,

http://www.ub.uit.no/munin/handle/10037/6902,

https://academic.microsoft.com/#/detail/1839470988