Abstract
With the fast development of genome sequencing technology, genome sequencing become faster and affordable. Consequently, genomic scientists are now facing an explosive increase of genomic data. Managing, storing and analyzing this quickly growing amount of data is challenging. It is desirable to apply some compression techniques to reduce storage and transferring cost. Referential genome compression is one of these techniques, which exploited the highly similarity of the same or an evolutionary close species (e.g., two randomly selected humans have at least 99% of genetic similarity) and store only the differences between the compressed file and well-known reference genome sequence. In this paper, we port two referential compression algorithm to Loongson platform and profiling their performance. And we use multi-process technology to improve the speed of compression.
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Acknowledgment
The research was jointly supported by Shenzhen Science & Technology Foundation: JCYJ20150930105133185, National Natural Science Foundation of China: NSF/GDU1301252, and State Key Laboratory of Computer Architecture ICTCA: CARCH 201405. Guangdong Province Key Laboratory Project: 2012A061400024.
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Du, Z., Guo, C., Zhang, Y., Luo, Q. (2017). Porting Referential Genome Compression Tool on Loongson Platform. In: Chen, G., Shen, H., Chen, M. (eds) Parallel Architecture, Algorithm and Programming. PAAP 2017. Communications in Computer and Information Science, vol 729. Springer, Singapore. https://doi.org/10.1007/978-981-10-6442-5_43
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DOI: https://doi.org/10.1007/978-981-10-6442-5_43
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