v-2.1.0

• Add --pretrained model flag for users to specify m6Anet models to be run
• Add m6Anet model trained on RNA004 kit
• Modify README to include installation and quickstart intructions

v-2.0.2

• Relax package requirement for m6anet
• Modify documentation to install using pip from source
• Add pytest-dependency custom mark for dataprep test

v-2.0.1

Github action on on publishing v-2.0.0 was run wrongly, resulting in users not being able to install the package from PyPI. This minor release fixes the issue

v-2.0.0

• Single entry point for all m6Anet functionalities such as m6anet dataprep, m6anet inference, and m6anet train
• Faster inference procedure by first saving individual read probability on data.indiv_proba.csv before sampling the required number of reads and averaging the calculated site probabilities
• Dataprep option to round data.json output to 3 decimal places
• Provides m6Anet model trained on Arabidopsis VIRc dataset from https://elifesciences.org/articles/78808 and the corresponding normalization factors

v-1.1.1

• Fixed torch version to prevent failed installation when latest version of pytorch is installed in a machine without GPU
• Fixed wrong naming convention with training demo data data.readcount.labelled
• Filter warning messages from pandas for less cluttering
• Fix typo m6anet-run_inference --infer_mod_rate flag (it is now --infer_mod_rate instead of --infer_mod-rate)

v-1.1.0

• Output kmer motif on the result file from m6anet-run_inference
• Add an option to automatically filter segments with low number of reads during m6anet-dataprep to reduce output size
• Add new functionality for pooling of reads from multiple replicates during training and inference
• Add new functionality for single molecule stoichiometry prediction
• Update to documentations

Version 1.0

• Minor bug fix on m6anet-dataprep (previous versions impose more stringent requirements on the number of neighboring positions)
• Removed unused arguments on dataprep and training scripts
• Documentation on m6anet-train command and formats of config files for training

Pre-release

• Fix a minor issue with indexing step in dataprep
• Fix typo in version numbers
• Remove unused files

Pre-release

A pre-release version of m6anet, it should run well with demo data but several functionalities have yet to be tested