Merge branch 'dev' into forMicroScope

.github/workflows/main.yml

@@ -120,7 +120,7 @@ jobs:
       shell: bash -l {0}
       run: |
         cd testingDataset
-        ppanggolin panrgp --anno genomes.gbff.list --cluster clusters.tsv --output readclusterpang --cpu $NUM_CPUS
+        ppanggolin panrgp --anno genomes.gbff.list --cluster clusters.tsv --output readclusterpang  --cpu $NUM_CPUS 
         ppanggolin annotate --anno genomes.gbff.list --output readclusters --cpu $NUM_CPUS
         ppanggolin cluster --clusters clusters.tsv -p readclusters/pangenome.h5 --cpu $NUM_CPUS
         ppanggolin msa --pangenome readclusterpang/pangenome.h5 --partition persistent --phylo -o readclusterpang/msa/ -f --cpu $NUM_CPUS

docs/user/PangenomeAnalyses/pangenomeCluster.md

@@ -54,6 +54,11 @@ You can do this from the command line:
 
 An example of what clusters.tsv should look like is provided [here](https://github.com/labgem/PPanGGOLiN/blob/master/testingDataset/clusters.tsv)
 
+```{note}
+When you provide your clustering, *PPanGGOLiN* will translate the representative gene sequence of each family and write it in the HDF5 file.
+```
+
+
 
 ### Defragmentation
 

ppanggolin/align/alignOnPang.py

@@ -27,7 +27,7 @@
 
 def align_seq_to_pang(target_seq_file: Union[Path, Iterable[Path]], query_seq_files: Union[Path, Iterable[Path]],
                       tmpdir: Path, cpu: int = 1, no_defrag: bool = False, identity: float = 0.8, coverage: float = 0.8,
-                      is_query_nt: bool = False, is_query_slf: bool = False, is_target_nt: bool = False,
+                      query_type: str = "unknow", is_query_slf: bool = False, target_type: str = "unknow",
                       is_target_slf: bool = False, translation_table: int = None) -> Path:
     """
     Align fasta sequence to pangenome sequences. 
@@ -39,34 +39,36 @@ def align_seq_to_pang(target_seq_file: Union[Path, Iterable[Path]], query_seq_fi
     :param no_defrag: Do not apply defragmentation
     :param identity: minimal identity threshold for the alignment
     :param coverage: minimal identity threshold for the alignment
-    :param is_query_nt: Is the sequence file (query) are nucleotide sequences. If True, sequences are translated by mmseqs
+    :param query_type: Sequences type of the file (query). [nucleotide, protein, unknow]
     :param is_query_slf: Is the sequence file (query) with single line fasta. If True, MMSeqs2 database will be with soft link
-    :param is_target_nt: Is the sequences of pangenome (target) are nucleotide sequences. If True, sequences are translated by mmseqs
+    :param target_type: Sequences type of pangenome (target). [nucleotide, aminoacid, protein]
     :param is_target_slf: Is the sequences of pangenome (target) with single line fasta. If True, MMSeqs2 database will be with soft link
     :param translation_table: Translation table to use, if sequences are nucleotide and need to be translated.
 
     :return: Alignment result file
     """
 
-    if is_target_nt:
+    if target_type == "nucleotide":
         logging.getLogger("PPanGGOLiN").debug("Target sequences will be translated by mmseqs with "
                                               f"translation table {translation_table}")
         with create_tmpdir(tmpdir, basename="target_db", keep_tmp=True) as target_db_dir:
             #  Keep is set as true because whether tmpdir is deleted or not target_db_dir will be the same
             target_db = translate_genes(target_seq_file, target_db_dir, cpu, is_target_slf, translation_table)
     else:
+        db_type = 1 if target_type == "protein" else 0
         target_db = create_mmseqs_db([target_seq_file] if isinstance(target_seq_file, Path) else target_seq_file,
-                                     'target_db', tmpdir, db_mode=1 if is_target_slf else 0, db_type=1)
+                                     'target_db', tmpdir, db_mode=1 if is_target_slf else 0, db_type=db_type)
 
-    if is_query_nt:
+    if query_type == "nucleotide":
         logging.getLogger("PPanGGOLiN").debug("Query sequences will be translated by mmseqs "
                                               f"with translation table {translation_table}")
         with create_tmpdir(tmpdir, basename="query_db", keep_tmp=True) as query_db_dir:
             #  Keep is set as true because whether tmpdir is deleted or not target_db_dir will be the same
             query_db = translate_genes(query_seq_files, query_db_dir, cpu, is_query_slf, translation_table)
     else:
+        db_type = 1 if query_type == "protein" else 0
         query_db = create_mmseqs_db([query_seq_files] if isinstance(query_seq_files, Path) else query_seq_files,
-                                    'query_db', tmpdir, db_mode=1 if is_query_slf else 0, db_type=1)
+                                    'query_db', tmpdir, db_mode=1 if is_query_slf else 0, db_type=db_type)
 
     cov_mode = "2"  # coverage of query
     if no_defrag:
@@ -390,7 +392,7 @@ def get_seq_info(seq_to_pang: dict, pangenome: Pangenome, output: Path, draw_rel
 
 
 def get_input_seq_to_family_with_rep(pangenome: Pangenome, sequence_files: Union[Path, Iterable[Path]], output: Path,
-                                     tmpdir: Path, is_input_seq_nt: bool, is_input_slf: bool = False, cpu: int = 1,
+                                     tmpdir: Path, input_type: str = "unknow", is_input_slf: bool = False, cpu: int = 1,
                                      no_defrag: bool = False, identity: float = 0.8, coverage: float = 0.8,
                                      translation_table: int = 11, disable_bar: bool = False
                                      ) -> Tuple[Path, Dict[str, GeneFamily]]:
@@ -404,7 +406,7 @@ def get_input_seq_to_family_with_rep(pangenome: Pangenome, sequence_files: Union
     :param sequence_files: Iterable of paths of FASTA files containing input sequences to align.
     :param output: Path to the output directory where alignment results will be stored.
     :param tmpdir: Temporary directory for intermediate files.
-    :param is_input_seq_nt: Is input sequence file nucleotide sequences.
+    :param input_type: Type of input sequence file. [nucleotide, aminoacid, unknow]
     :param is_input_slf: Is the sequence file with single line fasta. If True, MMSeqs2 database will be with soft link
     :param cpu: Number of CPU cores to use for the alignment (default: 1).
     :param no_defrag: If True, the defragmentation workflow is skipped (default: False).
@@ -421,18 +423,18 @@ def get_input_seq_to_family_with_rep(pangenome: Pangenome, sequence_files: Union
     logging.getLogger("PPanGGOLiN").debug(f'Write gene family sequences in {pangenome_sequences.absolute()}')
     write_gene_fam_sequences(pangenome, pangenome_sequences, add="ppanggolin_", disable_bar=disable_bar)
 
-    align_file = align_seq_to_pang(target_seq_file=pangenome_sequences, query_seq_files=sequence_files,
-                                   tmpdir=tmpdir, cpu=cpu, no_defrag=no_defrag, identity=identity, coverage=coverage,
-                                   is_query_nt=is_input_seq_nt, is_query_slf=is_input_slf,
-                                   is_target_nt=False, is_target_slf=True, translation_table=translation_table)
+    align_file = align_seq_to_pang(target_seq_file=pangenome_sequences, query_seq_files=sequence_files, tmpdir=tmpdir,
+                                   cpu=cpu, no_defrag=no_defrag, identity=identity, coverage=coverage,
+                                   query_type=input_type, is_query_slf=is_input_slf, is_target_slf=True,
+                                   target_type="protein", translation_table=translation_table)
 
     seq2pang, align_file = map_input_gene_to_family_rep_aln(align_file, output, pangenome)
 
     return align_file, seq2pang
 
 
 def get_input_seq_to_family_with_all(pangenome: Pangenome, sequence_files:  Union[Path, Iterable[Path]], output: Path,
-                                     tmpdir: Path, is_input_seq_nt: bool, is_input_slf: bool = False, cpu: int = 1,
+                                     tmpdir: Path, input_type: str = "unknow", is_input_slf: bool = False, cpu: int = 1,
                                      no_defrag: bool = False, identity: float = 0.8, coverage: float = 0.8,
                                      translation_table: int = 11, disable_bar: bool = False
                                      ) -> Tuple[Path, Dict[str, GeneFamily]]:
@@ -446,7 +448,7 @@ def get_input_seq_to_family_with_all(pangenome: Pangenome, sequence_files:  Unio
     :param sequence_files: Iterable of paths of FASTA files containing input sequences to align.
     :param output: Path to the output directory where alignment results will be stored.
     :param tmpdir: Temporary directory for intermediate files.
-    :param is_input_seq_nt: Is input sequence file nucleotide sequences.
+    :param input_type: Sequences type of the file (query). [nucleotide, protein, unknow]
     :param is_input_slf: Is the sequence file with single line fasta. If True, MMSeqs2 database will be with soft link
     :param cpu: Number of CPU cores to use for the alignment (default: 1).
     :param no_defrag: If True, the defragmentation workflow is skipped (default: False).
@@ -464,8 +466,8 @@ def get_input_seq_to_family_with_all(pangenome: Pangenome, sequence_files:  Unio
 
     align_file = align_seq_to_pang(target_seq_file=pangenome_sequences, query_seq_files=sequence_files, tmpdir=tmpdir,
                                    cpu=cpu, no_defrag=no_defrag, identity=identity, coverage=coverage,
-                                   is_query_nt=is_input_seq_nt, is_query_slf=is_input_slf, is_target_nt=True,
-                                   is_target_slf=True, translation_table=translation_table)
+                                   query_type=input_type, is_query_slf=is_input_slf, is_target_slf=True,
+                                   target_type="nucleotide", translation_table=translation_table)
 
     seq2pang, align_file = map_input_gene_to_family_all_aln(align_file, output, pangenome)
 
@@ -516,19 +518,19 @@ def align(pangenome: Pangenome, sequence_file: Path, output: Path, identity: flo
         seq_set, is_nucleotide, single_line_fasta = get_seq_ids(seqFileObj)
 
     with create_tmpdir(main_dir=tmpdir, basename="align_input_seq_tmpdir", keep_tmp=keep_tmp) as new_tmpdir:
-
+        input_type = "nucleotide" if is_nucleotide else "unknow"
         if use_representatives:
             align_file, seq2pang = get_input_seq_to_family_with_rep(pangenome, sequence_file, output, new_tmpdir,
-                                                                    is_input_seq_nt=is_nucleotide,
-                                                                    is_input_slf=single_line_fasta,
-                                                                    cpu=cpu, no_defrag=no_defrag, identity=identity,
+                                                                    input_type=input_type,
+                                                                    is_input_slf=single_line_fasta, cpu=cpu,
+                                                                    no_defrag=no_defrag, identity=identity,
                                                                     coverage=coverage,
                                                                     translation_table=translation_table,
                                                                     disable_bar=disable_bar)
         else:
             align_file, seq2pang = get_input_seq_to_family_with_all(pangenome=pangenome, sequence_files=sequence_file,
                                                                     output=output, tmpdir=new_tmpdir,
-                                                                    is_input_seq_nt=is_nucleotide,
+                                                                    input_type=input_type,
                                                                     is_input_slf=single_line_fasta,
                                                                     cpu=cpu, no_defrag=no_defrag, identity=identity,
                                                                     coverage=coverage,

ppanggolin/annotate/annotate.py

@@ -510,13 +510,11 @@ def read_org_gbff(organism_name: str, gbff_file_path: Path, circular_contigs: Li
                 rna_counter += 1
 
     genome_metadata, contig_to_uniq_metadata = combine_contigs_metadata(contig_to_metadata)
-
-    genome_meta_obj = Metadata(source='annotation_file', **genome_metadata)
-    organism.add_metadata(source="annotation_file", metadata=genome_meta_obj)
+
+    organism.add_metadata(metadata=Metadata(source='annotation_file', **genome_metadata))
 
     for contig, metadata_dict in contig_to_uniq_metadata.items():
-        contigs_meta_obj = Metadata(source='annotation_file', **metadata_dict)
-        contig.add_metadata(source="annotation_file", metadata=contigs_meta_obj)
+        contig.add_metadata(Metadata(source='annotation_file', **metadata_dict))
 
     if used_transl_table_arg:
         logging.getLogger("PPanGGOLiN").info(
@@ -791,8 +789,7 @@ def add_metadata_from_gff_file(contig_name_to_region_info: Dict[str, str], org:
     if len(contig_name_to_region_info) == org.number_of_contigs:
         genome_metadata, contig_to_uniq_metadata = combine_contigs_metadata(contig_name_to_region_info)
         if genome_metadata:
-            genome_meta_obj = Metadata(source='annotation_file', **genome_metadata)
-            org.add_metadata(source="annotation_file", metadata=genome_meta_obj)
+            org.add_metadata(Metadata(source='annotation_file', **genome_metadata))
     else:
         logging.getLogger("PPanGGOLiN").warning(
             f"Inconsistent data in GFF file {gff_file_path}: "
@@ -804,9 +801,8 @@ def add_metadata_from_gff_file(contig_name_to_region_info: Dict[str, str], org:
             contig = org.get(contig_name)
         except KeyError:
             raise ValueError(f"Contig '{contig_name}' does not exist in the genome object created from GFF file {gff_file_path}.")
-
-        contigs_meta_obj = Metadata(source='annotation_file', **metadata_dict)
-        contig.add_metadata(source="annotation_file", metadata=contigs_meta_obj)
+
+        contig.add_metadata(Metadata(source='annotation_file', **metadata_dict))
 
 
 def check_and_add_extra_gene_part(gene: Gene, new_gene_info: Dict, max_separation: int = 10):