BACKGROUND: Data from large Next Generation Sequencing (NGS) experiments present 
challenges both in terms of costs associated with storage and in time required 
for file transfer. It is sometimes possible to store only a summary relevant to 
particular applications, but generally it is desirable to keep all information 
needed to revisit experimental results in the future. Thus, the need for 
efficient lossless compression methods for NGS reads arises. It has been shown 
that NGS-specific compression schemes can improve results over generic 
compression methods, such as the Lempel-Ziv algorithm, Burrows-Wheeler 
transform, or Arithmetic Coding. When a reference genome is available, effective 
compression can be achieved by first aligning the reads to the reference genome, 
and then encoding each read using the alignment position combined with the 
differences in the read relative to the reference. These reference-based methods 
have been shown to compress better than reference-free schemes, but the 
alignment step they require demands several hours of CPU time on a typical 
dataset, whereas reference-free methods can usually compress in minutes.
RESULTS: We present a new approach that achieves highly efficient compression by 
using a reference genome, but completely circumvents the need for alignment, 
affording a great reduction in the time needed to compress. In contrast to 
reference-based methods that first align reads to the genome, we hash all reads 
into Bloom filters to encode, and decode by querying the same Bloom filters 
using read-length subsequences of the reference genome. Further compression is 
achieved by using a cascade of such filters.
CONCLUSIONS: Our method, called BARCODE, runs an order of magnitude faster than 
reference-based methods, while compressing an order of magnitude better than 
reference-free methods, over a broad range of sequencing coverage. In high 
coverage (50-100 fold), compared to the best tested compressors, BARCODE saves 
80-90% of the running time while only increasing space slightly.