Abstract
BioTest platform is dedicated for the processing of biomedical data that originate from various measurement techniques. This includes next-generation sequencing (NGS), that focuses the attention of researchers all of the world due to its broad possibilities in determining the structure of the DNA and RNA. However, the analysis of data provided by NGS requires large disk space, and is time-consuming, becoming a challenge for the data processing systems. In this paper, we have analyzed the possibility of scaling the BioTest platform in terms of genomic data analysis and platform architecture. Scalability tests were carried out using next-generation sequencing data and relied on methods for detection of somatic mutations and polymorphisms in the human DNA. Our results show that the platform is scalable, allowing to significantly reduce the execution time of performed calculations. However, the scalability capabilities depend on the experiment methodology and homogeneity of resources required by each task, which in NGS studies can be highly variable.
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Acknowledgements
This work was partially supported by The National Centre for Research and Development grant No. PBS3/B3/32/2015 and Strategmed2/267398/4/NCBR/2015. Presented system was developed and installed on the infrastructure of the Ziemowit computer cluster (www.ziemowit.hpc.polsl.pl) in the Laboratory of Bioinformatics and Computational Biology, The Biotechnology, Bioengineering and Bioinformatics Centre Silesian BIO-FARMA, created in the POIG.02.01.00-00-166/08 and expanded in the POIG.02.03.01-00-040/13 projects.
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Psiuk-Maksymowicz, K., Mrozek, D., Jaksik, R., Borys, D., Fujarewicz, K., Swierniak, A. (2017). Scalability of a Genomic Data Analysis in the BioTest Platform. In: Nguyen, N., Tojo, S., Nguyen, L., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2017. Lecture Notes in Computer Science(), vol 10192. Springer, Cham. https://doi.org/10.1007/978-3-319-54430-4_71
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DOI: https://doi.org/10.1007/978-3-319-54430-4_71
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