RLS Version 0.6

- Provide pretrained models from soil, cat gut, human oral, pig gut,
  mouse gut, built environment, wastewater and global (training from all
  environments).
- Add `check_install` command and run `check_install` before easy* command
- The user can now specify a pre-computed contig annotation table in
  mmseqs format
- Fix bug with non-standard characters in sample names (#68)
- Better subcommand names (`generate_sequence_features_*` and
  `generate_cannot_links`)

Author: luispedro

ChangeLog

@@ -1,11 +1,13 @@
-Unreleased
+Version 0.6.0 Mon 7 Feb 2022 by BigDataBiology
+	* Provide pretrained models from soil, cat gut, human oral,
+	pig gut, mouse gut, built environment, wastewater and global (training
+	from all environments).
 	* Add `check_install` command and run `check_install` before easy* command
 	* The user can now specify a pre-computed contig annotation table in
 	mmseqs format
 	* Fix bug with non-standard characters in sample names (#68)
-	* Provide pretrained models from soil, cat gut, human oral,
-	pig gut, mouse gut, built environment, wastewater and global (training
-	from all environments).
+	* Better subcommand names (`generate_sequence_features_*` and
+	`generate_cannot_links`)
 
 Version 0.5.0 Fri Jan 7 2022 by BigDataBiology
 	* Faster `SemiBin --version`

SemiBin/semibin_version.py

@@ -1 +1 @@
-__version__ = '0.5.0'
+__version__ = '0.6.0'

docs/faq.md

@@ -13,7 +13,7 @@ Yes. There are two approaches:
    formatted file and is likely to produce nonsensical results if a different
    format is provided.
 
-The approach one is more complex but can make sense as part of a larger
+The second approach is more complex but can make sense as part of a larger
 pipeline where taxonomic annotation of contigs is performed for multiple
 reasons (not only for the benefit of SemiBin).
 

docs/whatsnew.md

@@ -2,7 +2,11 @@
 
 ## Version 0.6
 
+*Released February 7 2022*
+
 ### User-visible improvements
+- Provide pretrained models from soil, cat gut, human oral,pig gut, mouse gut,
+  built environment, wastewater and global (training from all samples).
 - Users can now pass in the output of running mmseqs2 directly and SemiBin will
   use that instead of calling mmseqs itself (use option
   `--taxonomy-annotation-table`).
@@ -14,8 +18,6 @@
   `generate_sequence_features_multi` (for single- and multi-sample modes,
   respectively). The old names (`generate_data_single`/`generate_data_multi`)
   are kept as deprecated aliases.
-- Provide pretrained models from soil, cat gut, human oral,pig gut, mouse gut,
-  built environment, wastewater and global (training from all samples).
 - Add `check_install` command and run `check_install` before easy command
 
 ### Bugfixes

setup.py

@@ -11,14 +11,16 @@
       long_description = long_description,
       long_description_content_type = 'text/markdown',
       classifiers=[
-        'Development Status :: 3 - Alpha',
+        'Development Status :: 4 - Beta',
         'Intended Audience :: Science/Research',
         'Topic :: Scientific/Engineering :: Bio-Informatics',
         'Topic :: Scientific/Engineering :: Artificial Intelligence',
         'License :: OSI Approved :: MIT License',
         'Programming Language :: Python :: 3.7',
         'Programming Language :: Python :: 3.8',
         'Programming Language :: Python :: 3.9',
+        'Programming Language :: Python :: 3.10',
+        'Programming Language :: Python :: 3.11',
       ],
       url='https://github.com/BigDataBiology/SemiBin',
       author='Shaojun Pan',