# Compression of Next-Generation Sequencing Data and of DNA Digital Files +
## 5 Conclusions  
In this paper, different approaches for the compression of FASTQ, BAM, and SAM files generated by Next-Generation Sequencing tools containing nucleotide sequences have been analyzed.  
In the first part of the paper, the basic concepts of the application domain have been presented, for example: DNA sequencing workflow and the file formats generated by the machines used for NGS.  
The second part of our research discusses and evaluates the performance of the Quip compressor with respect to state-of-the-art generic compression tools, namely, gzip and bzip2.  
Quip is a specific compression system targeted to genetic files and developed in [6].  
Our testing results have been performed on a test data set that is very different from the one used in the experimental evaluation in [6], and they confirm the results in [6].  
The experimental evidences have shown that Quip is effective and outperforms gzip and bzip2 on almost all the files in our test data set.  
We have also presented a coding strategy for raw DNA data. We have experimented this coding strategy and we have compared it with the standard, one-dimensional data compression tools.  
The experimental results obtained are promising.  
Future research should involve a deeper experimentation of our coding strategy and the design of better compressors specifically based on this strategy.  
We are also considering approaches that combine data compression and data security for NGS data, following the approach in [29].  
\begin{table}
\begin{tabular}{c l c c} \hline \hline
**File** & **Algorithm** & **Compressed Size** & **Compression Ratio** \\ \hline \multirow{6}{*}{Mais (2,104,355,422 bytes)} & zip & 569,168,389 & 3.70 \\ \cline{2-4}  & gzip & 569,168,251 & 3.70 \\ \cline{2-4}  & bzip2 & 529,468,910 & 3.97 \\ \cline{2-4}  & Our coding & 537,100,232 & 3.91 \\ \cline{2-4}  & BWT + our coding & 496,965,993 & 4.23 \\ \cline{2-4}  & Our coding + zip & 502,914,200 & 4.18 \\ \cline{2-4}  & BWT + our coding + zip & 469,326,805 & 4.48 \\ \hline \multirow{6}{*}{Cricetus (2,320,022,665 bytes)} & zip & 654,051,291 & 3.55 \\ \cline{2-4}  & gzip & 654,051,149 & 3.55 \\ \cline{2-4}  & bzip2 & 609,362,970 & 3.81 \\ \cline{2-4}  & Our coding & 579,639,181 & 4.00 \\ \cline{2-4}  & BWT + our coding & 536,234,412 & 4.33 \\ \cline{2-4}  & Our coding + zip & 555,831,866 & 4.17 \\ \cline{2-4}  & BWT + our coding + zip & 534,583,442 & 4.34 \\ \hline \multirow{6}{*}{Pinus (20,547,720,415 bytes)} & zip & 5,763,264,652 & 3.57 \\ \cline{2-4}  & gzip & 5,763,264,397 & 3.57 \\ \cline{2-4}  & bzip2 & 5,479,811,899 & 3.75 \\ \cline{2-4}  & Our coding & 5,120,956,852 & 4.01 \\ \cline{2-4}  & BWT + our coding & 4,688,228,900 & 4.38 \\ \cline{2-4}  & Our coding + zip & 4,875,200,876 & 4.21 \\ \cline{2-4}  & BWT + our coding + zip & 4,522,676,308 & 4.54 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Experimental results (2).  
**Acknowledgments:** The author thanks the students of [PERSON] for conducting preliminary experiments on genomic data compression, and [PERSON], [PERSON], and [PERSON] for implementing and testing a preliminary version of a DNA compression algorithm related to the algorithm presented in Section 4.  
**Conflicts of Interest:** The authors declare no conflict of interest.