Upgrade of trim-low-abund for better, more profitable streaming.

Support for k-mer spectral error analysis, sublinear error profile calculations from shotgun data sets (sandbox/calc-error-profile.py), adaptive variant collection based on graphalign (sandbox/collect-variants.py), streaming error correction (sandbox/correct-errors.py), and streaming error trimming (sandbox/trim-low-abund.py).  The k-mer spectral error analysis and error profile/trimming is part of the 2014-streaming paper (https://github.com/ctb/2014-streaming).
Here we are trying to conservatively guess the position of errors; to do that, we have to look for places where low abundance and high abundance k-mers are immediately adjacent.  Yes, there may be other errors, but you can't tell just by looking at k-mer counts.