Quicklist

⚡ List of the main routines with standard arguments

• 🧠 Train a bmDCA model with default arguments:

adabmDCA train -d <fasta_file> -o <output_folder>

• 🔁 Resume training of a bmDCA model:

adabmDCA train -d <fasta_file> -o <output_folder> -p <file_params> -c <file_chains>

• 🌱 Train an eaDCA model with default arguments:

adabmDCA train -m eaDCA -d <fasta_file> -o <output_folder> --nsweeps 5

• 🔄 Resume training of an eaDCA model:

adabmDCA train -m eaDCA -d <fasta_file> -o <output_folder> -p <file_params> -c <file_chains>

• ✂️ Decimate a bmDCA model to 2% density:

adabmDCA train -m edDCA -d <fasta_file> -p <file_params> -c <file_chains>

• 🔀 Train and decimate a bmDCA model to 2% density:

adabmDCA train -m edDCA -d <fasta_file>

• 🧬 Generate sequences from a trained model:

adabmDCA sample -p <file_params> -d <fasta_file> -o <output_folder> --ngen <num_gen>

• 📉 Score a sequence set:

adabmDCA energies -d <fasta_file> -p <file_params> -o <output_folder>

• 🧪 Generate a single mutant library from a wild type:

adabmDCA DMS -d <WT> -p <file_params> -o <output_folder>

• 🔗 Compute contact scores via Frobenius norm:

adabmDCA contacts -p <file_params> -o <output_folder>

• 🔁 Reintegrate DCA model from experiments:

adabmDCA reintegrate -d <nat_msa> -o <output_folder> --reint <reint_msa> --adj <adj_vector> --alphabet <protein/rna>

• 🧠 Train/test split for homologous sequences:

adabmDCA profmark -t1 <t1> -t2 <t2> --bestof <n_trials> <output_prefix> <input_msa>