New in version 0.5.1

New in version 0.5

SAM/BAM format added! Users can now produce MSA files from their alignments in SAM format
README and INSTALL have been updated, and more information is available on the web, at the ShoRAH documentation page https://wiki-bsse.ethz.ch/display/ShoRAH/Documentation

dpm_sampler now computes Hamming distance in time proportional to the distance rather than to the length of the sequences.
dpm_sampler now clubs identical reads into objects. This method achieves a significant speed-up with Illumina datasets. Up to 65000 Illumina reads were analysed in a single window with good results.
freqEst sorts the output according to the frequency

dpm_sampler is now C++! Thanks to the structures defined in C++ libraries (map and multimap), we are able to run requiring much less memory
Parallelization! dec.py now calls diri_sampler using a pool of independent workers, exploiting all the available compuational power, as well as s2f.py does
The sampling has been improved, now we can have a more reliable estimate of the quality of our local haplotype reconstruction
The output of diri_sampler is now better organized (if -k is given, all intermediate files are saved in subdirectories of the current)
The alignment program runs now in linear time (with respect to the number of reads), and deals with indels in a more clever way
All python programs now use the logging module to write logs of their operations
plot_sampling.py and plot_stat.py can be used to produce graph showing the behaviour of the Gibbs sampling

New method to assign the reads after the sampling
The alignment is now provided by a separate program (step2far.py), so that the user can input his/her own alignment and install EMBOSS only if really necessary
Fixed numerical bugs when dealing with very high or very low probabilities