Software accompaniment to
Kao, W.C. and Song, Y.S.
naiveBayesCall: An efficient model-based base-calling algorithm for
Proc. 14th Annual Intl. Conf. on Research in Computational Molecular Biology
Lecture Notes in Computer Science 6044, pages 233--247.
Kao, W.C., Stevens, K., and Song, Y.S.
BayesCall: A model-based basecalling algorithm
for high-throughput short-read sequencing, Genome
Research, 19 (2009) 1884-1895.
[ Abstract ]
(A new base-calling algorithm that builds on our previous method
BayesCall to achieve scalability.)
[ Abstract ]
Files can be downloaded using "Save Link/Target As..."
This software is available under the GNU General Public License.
(October 28, 2009)
a new basecalling method that builds on our previous
is included in the new release and enabled by default.
an efficient base-calling algorithm that is orders of magnitude
faster than BayesCall, while still maintaining a comparably high level of
(August 6, 2009) Using the model
proprosed in our Genome Research paper, we are in the process of
developing a new method that is orders of magnitude faster than our current implementation,
while maintaining a comparable accuracy. This new version will be
- Version 0.3
- A new basecalling method that is order of magnitude faster
than the original one, while still maintaining a comparably high level of
- Now comes with -ncpu option.
- Training and testing can take multiple intensity files at the same time.
- Version 0.2
- Improved memory management (faster training and testing).
- Suppress verbose console outputs.