Version 0.3.0

Version 0.3

Release 10 August 2021

User-visible improvements

• Support training from several samples
• Remove output_bin_path if output_bin_path exists
• Make several internal parameters configuable: (1) minimum length of contigs to bin (--min-len parameter); (2) minimum length of contigs to break up in order to generate must-link constraints (--ml-threshold parameter); (3) the ratio of the number of base pairs of contigs between 1000-2500 bp smaller than this value, the minimal length will be set as 1000bp, otherwise 2500bp (--ratio parameter).
• Add -p argument for predict_taxonomy mode

Internal improvements

• Better code overall
• Fix np.concatenate warning
• Remove redundant matrix when clustering
• Better pretrained models
• Faster calculating dapth using Numpy
• Use correct number of threads in kneighbors_graph()

Bugfixes

• Respect number of threads (-p argument) when training (issue 34)

Version 0.2.0

First release under the name SemiBin

Full ChangeLog (see also https://semibin.readthedocs.io/en/latest/whatsnew/):

• Change name to SemiBin
• Add support for training with several samples
• Test with Python 3.9
• Download mmseqs database with --remove-tmp-file 1
• Better output names
• Fix bugs when paths have spaces
• Fix installation issues by listing all the dependencies
• Add download_GTDB command
• Add --no-recluster option
• Add --environment option
• Add --mode option
• All around more robust code by including more error checking & testing
• Better built-in models

Release 0.1.1

First release.

Can perform both single-sample and multi-sample binning.