Scoary

- Fixed a bug that would cause Scoary to crash if ran without any -c options.

- Fixed a bug where results in the output file did not have quotes around them. This could interfere with annotations that have delimiters (like commas) in them.

- The correction options are now a lot more sophisticated, and allow multiple restrictions with individual p-values to be set.
- Fixed a bug that would sometimes result in a too strict Bonferroni p-value in the results.
- No-time now also applies to the reduced gene presence/absence file.
- The results sorting now works a little differently. When using only pairwise comparisons filtering, results will be sorted by these p-values. When other filters (Individual, Bonferroni, Benjamini-Hochberg) are used, results will be sorted by these instead.
- Fixed a bug where the program would crash if you specified a very large max_hits.
- The citation option has been added, and includes a nifty ASCII logo.
- Some optimization when using pairwise comparison to filter results.

- The no-time argument can now be used to avoid output files (results and tree file) to come with a timestamp in the name. Should make it easier to implement Scoary in automated pipelines. (Credits: Marco Galardini)
- Comma is now the default delimiter in input and output files. The user can specify another input/output delimiter with the delimiter argument. (Note that the two input files and the output files will all have the same delimiter)
- Bug fixes that caused python3 problems in 1.3.6 (Credits: Marco Galardini)

- Simulated example data is included in the exampledata folder. This is primarily intended as a guide to how input files can look, as well as giving users a quick view at what the program can do. Running Scoary with the --test flag will overrun all other options (except --version) and automatically run the exampledata with default options.

- You can now use the -w option with -r to write a reduced gene presence/absence file containing only the subset isolates. This ensures that the program will run much faster if you have a large dataset (1000s of isolates) but only want to analyze a subset. Scoary automatically opens and analyzes the newly written file.
- This is a pre-release version. There might still be bugs in the code, in which case I would be grateful if you report them.