1.0.2

1.0.2 (2023-05-19)

This release uses models built on [GTDB release 202].
This release uses the DIAMOND database version 2, available at DOI [10.5281/zenodo.5571251].

Models and database are unchanged from v 1.0.1, output results should be the same.

This is a minor release that does not impact any previous CheckM2 functionality. New features in this release:

• Fixed some warnings when no protein file was generated
• CheckM2 now reports the total number of contigs as well as max contig length
• Better command-line suggestions for 'predict' function
• Fixes to setup.py reduce potential conda environment conflicts
• Updated README to include mamba installation
• Minor grammatical fixes to command-line usage

Next major CheckM2 release will incorporate updated models that were trained on high-quality genomes in GTDB release 214

1.0.1

1.0.1 (2023-01-22)

This release uses models built on [GTDB release 202].
This release uses the DIAMOND database version 2, available at DOI [10.5281/zenodo.5571251].

Models and database are unchanged from v 1.0.0, output results should be the same.

New features in this release:

• You can specify an alternate temporary directory for CheckM2 using --tmpdir in case the default is limited in space (addresses #35)
• Added a --database_path option to checkm2 predict. If you have a downloaded CheckM2 database but cannot set it via checkm2 database --setdblocation, you can provide the path to checkm2 predict instead. (addresses #15)
• Logging now notes CheckM2 version
• CheckM2 Version 1.0.1 onwards is now available on bioconda and pypi.

New bugfixes in this release:

• CheckM2 won't crash when calculating GC content of fasta files with lowercase bases (addresses #37)
• CheckM2 now correctly calculates GC content of all sequences in the fasta file instead of the last one
• Fixed database download version check failure that would sometimes occur (addresses #31)

1.0.0

1.0.0 (2022-12-16)

First official release of CheckM2!

This release uses models built on [GTDB release 202].
This release uses the DIAMOND database version 2, available at DOI [10.5281/zenodo.5571251].

Models and database are unchanged from v 0.1.3, output results should be the same.

New features in this release:

• CheckM2 now has tagged releases and a changelog summary. This addresses (#25, #22), as well as allows submission to PyPI and Bioconda (#29, #7)
• CheckM2 now has logging enabled by default. Logs will be saved in the output folder in the file 'checkm2.log' (Resolves #2)
• You can now optionally remove intermediate files (protein files and diamond output) using the --remove_intermediates option (Resolves #3)
• CheckM2 now checks for diamond database and loads machine learning models before proceeding with main workflow (Resolves #4)
• CheckM2 now reports coding density for bins, as well as contig N50, average gene size, genome length and GC content. This gives the user more information and can help identify issues such as e.g. frameshift-dominated genomes
• Processing feature vectors and predicting completeness and contamination is now chunked by groups of genomes (default 250) instead of holding all feature vectors in memory. This drastically reduces RAM usage by CheckM2.
• You can now specify a specific coding table that Prodigal should use for your bins using the --ttable flag. By default, CheckM2 chooses between 4 or 11 based on coding density information.
• CheckM2 now forces tensorflow models to run using CPU (this should address #26, #12). For better compatibility, it is strongly suggested to initially install the CheckM2 conda environment on a computer without a GPU
• CheckM2 should now use tensorflow release < 2.6.0 (this should address #16)
• CheckM2 can reuse prodigal and diamond output using the --resume flag (addresses #13, thanks to JeanMainguy for implementation)