v-2.0.0

[chrishendra93]

• 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

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This discussion was created from the release v-2.0.0.