Software Citation
-----------------

If you use the khmer software, you must cite:

   Crusoe et al., The khmer software package: enabling efficient
   sequence analysis. 2014. doi: 10.6084/m9.figshare.979190

If you use any of our published scientific methods, you should *also*
cite the relevant paper(s), as directed below.

Graph partitioning and/or compressible graph representation
-----------------------------------------------------------

The load-graph.py, partition-graph.py, find-knots.py, load-graph.py,
and partition-graph.py scripts are part of the compressible graph
representation and partitioning algorithms described in:

   Pell J, Hintze A, Canino-Koning R, Howe A, Tiedje JM, Brown CT.
   Proc Natl Acad Sci U S A. 2012 Aug 14;109(33):13272-7.
   doi: 10.1073/pnas.1121464109.
   PMID: 22847406

Digital normalization
----------------------

The normalize-by-median.py and count-median.py scripts are part of
the digital normalization algorithm, described in:

   A Reference-Free Algorithm for Computational Normalization of
   Shotgun Sequencing Data
   Brown CT, Howe AC, Zhang Q, Pyrkosz AB, Brom TH
   arXiv:1203.4802 [q-bio.GN]
   http://arxiv.org/abs/1203.4802

K-mer counting
--------------

The abundance-dist.py, filter-abund.py, and load-into-counting.py scripts
implement the probabilistic k-mer counting described in:

   These are not the k-mers you are looking for: efficient online k-mer counting using a probabilistic data structure
   Zhang Q, Pell J, Canino-Koning R, Howe AC, Brown CT.
   arXiv:1309.2975 [q-bio.GN]
   http://arxiv.org/abs/1309.2975
