SeqUtils

Library for sequence processing

prokbert.sequtils.load_contigs(fasta_files_list)	Loads contigs from a list of FASTA files.
prokbert.sequtils.segment_sequence_contiguous(...)	Creates end-to-end, disjoint segments of a sequence without overlaps.
prokbert.sequtils.segment_sequences_random(...)	Randomly segments the input sequences.
prokbert.sequtils.segment_sequences(...[, ...])	Segments sequences based on the provided parameters.
prokbert.sequtils.lca_tokenize_segment(...)	Tokenizes a single segment using Local Context Aware (LCA) tokenization.
prokbert.sequtils.tokenize_kmerized_segment_list(...)	Tokenizes or vectorizes a list of k-merized segments into a list of token vectors.
prokbert.sequtils.process_batch_tokenize_segments_with_ids(...)	Tokenizes a batch of segments and associates them with their provided IDs.
prokbert.sequtils.batch_tokenize_segments_with_ids(...)	Parallel tokenization of segments with associated IDs.
prokbert.sequtils.get_rectangular_array_from_tokenized_dataset(...)	Create a rectangular numpy array that can be used as input to a Language Model (LM) from tokenized segment data.
prokbert.sequtils.pretty_print_overlapping_sequence(...)	Format the sequence for pretty printing with overlapping k-mers.
prokbert.sequtils.generate_kmers(abc, k)	Generates all possible k-mers from a given alphabet.
prokbert.sequtils.save_to_hdf(X, hdf_file_path)	Save a numpy array and an optional pandas DataFrame to an HDF5 file.