GReEn: a tool for efficient compression of genome resequencing data

Abstract

Research in the genomic sciences is confronted with the volume of sequencing and resequencing data increasing at a higher pace than that of data storage and communication resources, shifting a significant part of research budgets from the sequencing component of a project to the computational one. Hence, being able to efficiently store sequencing and resequencing data is a problem of paramount importance. In this article, we describe GReEn (Genome Resequencing Encoding), a tool for compressing genome resequencing data using a reference genome sequence. It overcomes some drawbacks of the recently proposed tool GRS, namely, the possibility of compressing sequences that cannot be handled by GRS, faster running times and compression gains of over 100-fold for some sequences. This tool is freely available for non-commercial use at ftp://ftp.ieeta.pt/~ap/codecs/GReEn1.tar.gz.

Figure 1.

The copy model. In this example, the copy model was restarted at position 341 587 of the reference sequence, corresponding to position 327 829 of the target sequence. Since then, it has correctly predicted 5 characters, if the case is considered, and a total of 11 characters if the case is ignored. The dashed arrow indicates a failed prediction. According to this example, the next character to be predicted is ‘G’.

Figure 2.

Data organized in a hash table.