thoraxe package

Subpackages

• thoraxe.add_transcripts package
  • Submodules
  • thoraxe.add_transcripts.add_transcripts module
    • Paths
      • Paths.exontable
      • Paths.input
      • Paths.sequences
      • Paths.tsl
    • add_sequences()
    • add_to_exontable()
    • add_to_tsl()
    • check_input()
    • get_output_paths()
    • main()
    • parse_command_line()
    • read_fasta()
  • Module contents
• thoraxe.subexons package
  • Submodules
  • thoraxe.subexons.alignment module
    • ColCluster
    • ColPattern
      • ColPattern.end
      • ColPattern.pattern
      • ColPattern.start
    • ProblematicSubexonBlock
      • ProblematicSubexonBlock.block_type
      • ProblematicSubexonBlock.gap_block_end
      • ProblematicSubexonBlock.gap_block_start
      • ProblematicSubexonBlock.sequence_index
      • ProblematicSubexonBlock.subexon
      • ProblematicSubexonBlock.subexon_block_end
      • ProblematicSubexonBlock.subexon_block_start
      • ProblematicSubexonBlock.subexon_blocks
    • cluster_subexon_blocks()
    • column_clusters()
    • column_patterns()
    • create_chimeric_sequences()
    • create_msa_matrix()
    • create_subexon_matrix()
    • delete_padding()
    • delete_subexons()
    • disintegration()
    • gene2species()
    • get_consensus()
    • get_gene_ids()
    • get_subexon_boundaries()
    • get_submsa()
    • impute_missing_s_exon()
    • move_block()
    • move_problematic_block_clusters()
    • move_subexon_block()
    • msa2sequences()
    • msa_matrices()
    • problematic_block_clusters()
    • problematic_subexon_blocks()
    • read_msa_fasta()
    • resume_seq()
    • run_aligner()
    • save_s_exons()
    • score_solution()
    • sort_species()
    • subexon_connectivity()
  • thoraxe.subexons.ases module
    • PathData
      • PathData.Genes
      • PathData.Transcripts
    • conserved_ases()
    • create_ases_table()
    • detect_ases()
    • get_transcript_scores()
    • read_splice_graph()
  • thoraxe.subexons.graph module
    • nodes_and_edges2genes_and_transcripts()
    • splice_graph_gml()
  • thoraxe.subexons.phylosofs module
    • get_s_exon2char()
    • get_transcript2phylosofs()
    • phylosofs_inputs()
    • prune_tree()
  • thoraxe.subexons.plot module
    • create_python_structure()
    • plot_msa_subexons()
  • thoraxe.subexons.rescue module
    • get_unaligned_regions()
    • modify_subexon_cluster()
    • subexon_rescue_phase()
  • thoraxe.subexons.subexons module
    • Interval
      • Interval.components
      • Interval.end
      • Interval.start
    • create_subexon_table()
    • disjoint_intervals()
    • update_to_merge_list()
  • thoraxe.subexons.tidy module
    • get_tidy_table()
  • Module contents
• thoraxe.transcript_info package
  • Submodules
  • thoraxe.transcript_info.clusters module
    • cluster2str()
    • fill_clusters()
    • inform_about_deletions()
    • set_to_delete()
  • thoraxe.transcript_info.exon_clustering module
    • align()
    • coverage()
    • coverage_shortest()
    • exon_clustering()
    • percent_identity()
  • thoraxe.transcript_info.phases module
    • bases_to_complete_next_codon()
    • bases_to_complete_previous_codon()
    • calculate_phase()
    • check_order_and_phases()
    • end_phase_previous_exon()
  • thoraxe.transcript_info.transcript_info module
    • add_exon_sequences()
    • add_protein_seq()
    • delete_badquality_sequences()
    • delete_identical_sequences()
    • delete_incomplete_sequences()
    • find_identical_exons()
    • find_identical_sequences()
    • merge_identical_exons()
    • read_exon_file()
    • read_transcript_info()
    • read_tsl_file()
    • store_cluster()
  • Module contents
• thoraxe.transcript_query package
  • Submodules
  • thoraxe.transcript_query.transcript_query module
    • dictseq2fasta()
    • filter_ortho()
    • generic_ensembl_rest_request()
    • get_biomart_exons_annot()
    • get_exons_sequences()
    • get_geneids_from_symbol()
    • get_genetree()
    • get_listofexons()
    • get_listoftranscripts()
    • get_orthologs()
    • get_transcripts_orthologs()
    • is_esemble_id()
    • lodict2csv()
    • main()
    • parse_command_line()
    • save_ensembl_version()
    • write_tsl_file()
  • Module contents
• thoraxe.utils package
  • Submodules
  • thoraxe.utils.folders module
    • create_subfolder()
  • thoraxe.utils.species module
    • check_species_name()
    • get_species_list()
  • thoraxe.utils.split module
    • split_exons()
    • split_lengths()
    • split_seqs()
  • thoraxe.utils.windows module
    • is_windows()
  • Module contents

Submodules

thoraxe.thoraxe module

ThorAxe pipeline and script functions.

thoraxe.thoraxe.add_s_exon_phases_and_coordinates(tbl)

Add s-exon genomic coordinates and phases to the tidy s-exon table.

For each s-exon, it add the S_exon_Genomic_Sequence and their genomic coordinates, starting at 1 and defining the closed interval: [S_exon_CodingStart, S_exon_CodingEnd]. Where S_exon_CodingStart is greater or equal to S_exon_CodingEnd for genes in the reverse Strand. It add also the S_exon_StartPhase and S_exon_EndPhase for those intervals.

An s-exon, defined at the protein level, can be an entire sub-exon or a part of it. In cases where an s-exon is identical to a sub-exon, the genomic coordinates and the phases are the same. However, when a sub-exon is split into several s-exons, coordinates and phases need to be calculated:

Example 1: s-exons in the positive strand.

The following sub-exon shares codons with the previous and following sub-exon. In this example, - represents introns and lower case characters represent exon nucleotides. The start and end phases are 1 and 2 respectively:

...v----vvwwwxxxyyyzz-----z...

Because we are in the positive strand, the residue V coming from the vvv shared codon is assigned to this sub-exon protein sequence. In the same way, the Z residue coming from the zzz shared exon is assigned to the beginning of the next sub-exon:

VWXY

Let’s say that this sub-exon is composed of two s-exons: VW and XY. Then the corresponding genomic sequences are vvwww and xxxyyyzz and the (start, end) phases are (1, 0) and (0, 2).

Genomic coordinates.

Let’s say that the first v has the genomic coordinate 1:

v ---- vvwww xxxyyyzz ----- z `` 1 11111111 12222 2`` 1 2345 67890 12345678 90123 4

In this way, the first s-exon has the genomic coordinates [6, 10] and the second has the genomic coordinates [11, 18]. The first s-exon has 2 amino-acid residues, but 5 instead of 6 bases because the first codon is shared between two s-exons. In particular, the amino-acid residue V needs two bases in this s-exon to complete the codon started in the previous s-exon.

Example 2: s-exons in the negative strand.

v ---- vvwww xxxyyyzz ----- z 2 2222 11111 11111           `` ``4 3210 98765 43210987 65432 1

If the same sequence belongs to the negative strand, the sub-exon protein sequence is going to contain Z but not V: WXYZ. Therefore, possible s-exons are W and XYZ and the corresponding genomic sequences will be vvwww and xxxyyyzz and the (start, end) phases will be (1, 0) and (0, 2).

In this way, the first s-exon has the genomic coordinates [19, 15] and the second has the genomic coordinates [14, 7]. The first s-exon has ` 1` amino-acid residue, but 5 instead of 3 bases because the first codon is shared between two s-exons. In particular, the amino-acid residue V needs two bases in this s-exon to complete the codon started in the previous s-exon.

thoraxe.thoraxe.create_chimeric_msa(output_folder, subexon_table, gene2speciesname, connected_subexons, clusters=None, cutoff=30.0, min_col_number=4, aligner='ProGraphMSA', padding='XXXXXXXXXX', species_list=None, keep_single_subexons=False)

Return a dict from cluster to cluster data.

For each cluster, there is a tuple with the subexon dataframe, the chimeric sequences and the msa.

This function can take a clusters argument with the list of ‘Cluster’ identifiers to use. If that list is not given, all the positive ‘Cluster’ identifiers from subexon_table are used.

thoraxe.thoraxe.get_s_exon_msas(output_folder)

Return a dict of the s_exon MSAs.

thoraxe.thoraxe.get_s_exons(output_folder, subexon_table, gene2speciesname, connected_subexons, minimum_len=4, coverage_cutoff=80.0, percent_identity_cutoff=30.0, gap_open_penalty=10, gap_extend_penalty=1, aligner='ProGraphMSA', padding='XXXXXXXXXX', movements=True, disintegration=True, species_list=None, keep_single_subexons=False)

Perform almost all the ThorAxe pipeline.

thoraxe.thoraxe.get_subexons(transcript_table, minimum_len=4, coverage_cutoff=80.0, percent_identity_cutoff=30.0, gap_open_penalty=10, gap_extend_penalty=1)

Return a DataFrame with subexon information and clustered exons.

Exons are clustered according to their protein sequence using the blosum50 matrix and the following arguments: minimum_len, coverage_cutoff, percent_identity_cutoff, gap_open_penalty and gap_extend_penalty.

thoraxe.thoraxe.get_transcripts(input_folder, max_tsl_level=3.0, species_list=None)

Return a DataFrame with the transcript information.

thoraxe.thoraxe.main()

Perform Pipeline.

thoraxe.thoraxe.merge_clusters(subexon_table)

Merge ‘Cluster’s that share subexons.

thoraxe.thoraxe.parse_command_line()

Parse command line.

It uses argparse to parse thoraxe’ command line arguments and returns the argparse parser.

thoraxe.thoraxe.update_subexon_table(subexon_table, cluster2data)

Update the subexon table by adding the s-exon information.

thoraxe.version module

Module contents

thoraxe: Pipeline to disentangle homology relationships between exons.