  Motivation:
  Rapid technological progress in DNA sequencing has stimulated interest in
compressing the vast datasets that are now routinely produced. Relatively
little attention has been paid to compressing the quality scores that are
assigned to each sequence, even though these scores may be harder to compress
than the sequences themselves. By aggregating a set of reads into a compressed
index, we find that the majority of bases can be predicted from the sequence of
bases that are adjacent to them and hence are likely to be less informative for
variant calling or other applications. The quality scores for such bases are
aggressively compressed, leaving a relatively small number at full resolution.
Since our approach relies directly on redundancy present in the reads, it does
not need a reference sequence and is therefore applicable to data from
metagenomics and de novo experiments as well as to resequencing data.
  Results:
  We show that a conservative smoothing strategy affecting 75% of the quality
scores above Q2 leads to an overall quality score compression of 1 bit per
value with a negligible effect on variant calling. A compression of 0.68 bit
per quality value is achieved using a more aggressive smoothing strategy, again
with a very small effect on variant calling.
  Availability:
  Code to construct the BWT and LCP-array on large genomic data sets is part of
the BEETL library, available as a github respository at
http://git@github.com:BEETL/BEETL.git .
