From 8774d3c100402860467a82b773c71980247e2163 Mon Sep 17 00:00:00 2001 From: Oliver Schwengers Date: Thu, 10 Oct 2024 08:57:28 +0200 Subject: [PATCH] introduce user-provided hmms (#327) * fix table in readme * add hmm parameter * bump PyHMMER dependency to 0.10.14 * introduce MIN_HMM_EVALUE constant * implement HMM search * add tests * adjust ranks of user-provided proteins and HMMs Increase the rank of user-provided proteins to 101, so that they have higher ranks than user-provided HMMs, which in turn are ranked 100, thus higher than all non-user-provided annotation sources. * print user hmm parameter to stdout * add hmms to readme * remove orf debug print * finish user-hmm feature * polish readme * add a second test HMM with short description format * discard hmm hit source * refactor expert hit annotation selection * take into account annotation score to rank/score equal expert hits * bump PyHMMER version to 0.10.15 --- README.md | 26 +- bakta/config.py | 16 +- bakta/constants.py | 1 + bakta/expert/protein_hmms.py | 73 + bakta/expert/protein_sequences.py | 2 +- bakta/features/annotation.py | 62 +- bakta/features/orf.py | 2 +- bakta/main.py | 13 +- bakta/proteins.py | 43 +- bakta/utils.py | 1 + environment.yml | 2 +- setup.py | 2 +- test/data/NF000185.2.HMM | 2316 +++++++++++++++++++++++++++++ test/test_args.py | 21 + test/test_bakta.py | 1 + 15 files changed, 2529 insertions(+), 52 deletions(-) create mode 100644 bakta/expert/protein_hmms.py create mode 100644 test/data/NF000185.2.HMM diff --git a/README.md b/README.md index b591631f..b2a5ee98 100644 --- a/README.md +++ b/README.md @@ -240,8 +240,8 @@ original locus id | new locus id | type | topology | name NODE_1 | chrom | `chromosome` | `circular` | `-` NODE_2 | p1 | `plasmid` | `c` | `pXYZ1` NODE_3 | p2 | `p` | `c` | `pXYZ2` -NODE_4 | special-contig-name-xyz | `-` | - -NODE_5 | `` | `-` | - +NODE_4 | special-contig-name-xyz | `-` | `-` | `-` +NODE_5 | `` | `-` | `-` | `-` #### User-provided regions @@ -274,6 +274,27 @@ dbxrefs | ``, `db:id`, `,` separated list | `VFDB:VF0511` Protein sequences provided in short Fasta or GenBank format are searched with default thresholds of 90%, 80% and 80% for minimal identity, query and subject coverage, respectively. +#### User-provided HMMs + +Bakta accepts user-provided trusted HMMs via `--hmms` in HMMER's text format. If set, Bakta will adhere to the *trusted cutoff* specified in the HMM header. In addition, a max. evalue threshold of 1e-6 is applied. By default, Bakta uses the HMM description line as a product description. Further information can be provided via the HMM description line using the *short* format as explained above in the [User-provided protein sequences](####user-provided-protein-sequences) section. + +```bash +# default +HMMER3/f [3.1b2 | February 2015] +NAME id +ACC id +DESC product +LENG 435 +TC 600 600 + +# short +NAME id +ACC id +DESC gene~~~product~~~dbxrefs +LENG 435 +TC 600 600 +``` + ### Output Annotation results are provided in standard bioinformatics file formats: @@ -394,6 +415,7 @@ Annotation: Replicon information table (tsv/csv) --regions REGIONS Path to pre-annotated regions in GFF3 or Genbank format (regions only, no functional annotations). --proteins PROTEINS Fasta file of trusted protein sequences for CDS annotation + --hmms HMMS HMM file of trusted hidden markov models in HMMER format for CDS annotation --meta Run in metagenome mode. This only affects CDS prediction. Workflow: diff --git a/bakta/config.py b/bakta/config.py index 6cb419e0..c8f35086 100644 --- a/bakta/config.py +++ b/bakta/config.py @@ -55,6 +55,7 @@ replicons = None compliant = None user_proteins = None +user_hmms = None meta = None regions = None @@ -162,7 +163,7 @@ def setup(args): taxon = None # annotation configurations - global complete, prodigal_tf, translation_table, keep_contig_headers, locus, locus_tag, locus_tag_increment, gram, replicons, compliant, user_proteins, meta, regions + global complete, prodigal_tf, translation_table, keep_contig_headers, locus, locus_tag, locus_tag_increment, gram, replicons, compliant, user_proteins, user_hmms, meta, regions complete = args.complete log.info('complete=%s', complete) prodigal_tf = args.prodigal_tf @@ -236,6 +237,19 @@ def setup(args): sys.exit(f'ERROR: replicon table file ({replicons}) not valid!') log.info('replicon-table=%s', replicons) user_proteins = check_user_proteins(args) + user_hmms = args.hmms + if(user_hmms is not None): + try: + if(user_hmms == ''): + raise ValueError('File path argument must be non-empty') + user_hmms_path = Path(user_hmms).resolve() + check_readability('HMM', user_hmms_path) + check_content_size('HMM', user_hmms_path) + user_hmms = user_hmms_path + except: + log.error('provided HMM file not valid! path=%s', user_hmms) + sys.exit(f'ERROR: HMM file ({user_hmms}) not valid!') + regions = args.regions if(regions is not None): try: diff --git a/bakta/constants.py b/bakta/constants.py index b42df59d..b9e7e83f 100644 --- a/bakta/constants.py +++ b/bakta/constants.py @@ -26,6 +26,7 @@ MIN_PSC_IDENTITY = 0.9 # min protein identity for PSC detection MIN_SORF_COVERAGE = 0.9 # min sORF coverage for PSC detection MIN_SORF_IDENTITY = 0.9 # min sORF identity for PSC detection +MIN_HMM_EVALUE = 1e-6 # min evalue for CDS HMM searches HYPOTHETICAL_PROTEIN = 'hypothetical protein' # hypothetical protein product description CDS_MAX_OVERLAPS = 30 # max overlap [bp] allowed for user-provided/de novo-predicted CDS overlaps CDS_SOURCE_USER = 'user-provided' diff --git a/bakta/expert/protein_hmms.py b/bakta/expert/protein_hmms.py new file mode 100644 index 00000000..6661f3f8 --- /dev/null +++ b/bakta/expert/protein_hmms.py @@ -0,0 +1,73 @@ +import logging + +from typing import Sequence + +import pyhmmer + +import bakta.config as cfg +import bakta.constants as bc +import bakta.features.orf as orf + + +log = logging.getLogger('EXPERT_AA_HMM') + + +def search(cdss: Sequence[dict], user_hmms_path): + """Detect Pfam-A entries""" + cds_found = set() + orf_by_aa_digest = orf.get_orf_dictionary(cdss) + alphabet: pyhmmer.easel.Alphabet = pyhmmer.easel.Alphabet.amino() + proteins: list[pyhmmer.easel.DigitalSequence] = [ pyhmmer.easel.TextSequence(sequence=cds['aa'], name=bytes(orf.get_orf_key(cds), 'UTF-8')).digitize(alphabet) for cds in cdss ] + with pyhmmer.plan7.HMMFile(user_hmms_path) as hmms_fh: + hmms = list(hmms_fh) + for hmm_query_hits in pyhmmer.hmmsearch(hmms, proteins, bit_cutoffs='trusted', cpus=cfg.threads): + hmm_id = hmm_query_hits.query.accession.decode() + hmm_length = hmm_query_hits.query.M + hmm_description = hmm_query_hits.query.description.decode() + hmms_description_fields = hmm_description.split('~~~') + for hmm_query_hit in hmm_query_hits.reported: + aa_identifier = hmm_query_hit.name.decode() + cds = orf_by_aa_digest[aa_identifier] + if hmm_query_hit.evalue > bc.MIN_HMM_EVALUE: + log.debug( + 'discard low evalue: contig=%s, start=%i, stop=%i, strand=%s, id=%s, evalue=%1.1e, bitscore=%f', + cds['contig'], cds['start'], cds['stop'], cds['strand'], hmm_id, hmm_query_hit.evalue, hmm_query_hit.score + ) + else: + hit_domain_lengths_sum = sum([len(dom.alignment.hmm_sequence) for dom in hmm_query_hit.domains.included]) + hit = { + 'type': 'user_hmms', + 'rank': 100, + 'id': hmm_id, + 'length': hit_domain_lengths_sum, + 'aa_cov': hit_domain_lengths_sum / len(cds['aa']), + 'hmm_cov': hit_domain_lengths_sum / hmm_length, + 'evalue': hmm_query_hit.evalue, + 'score': hmm_query_hit.score, + 'start': hmm_query_hit.best_domain.alignment.target_from, + 'stop': hmm_query_hit.best_domain.alignment.target_to, + 'db_xrefs': [f'UserHMM:{hmm_id}'], + 'gene': None, + 'product': None + } + # read user-provided gene, product, db_xrefs via HMM's description field provided as ~~~~~~ + if(len(hmms_description_fields) == 1): + hit['product'] = hmm_description if hmm_description != '' else None + elif(len(hmms_description_fields) == 3): + (gene, product, dbxrefs) = hmms_description_fields + hit['gene'] = gene + hit['product'] = product + hit['db_xrefs'].extend(set(dbxrefs.split(','))) + else: + log.warning('wrong HMM description format: id=%s, desc=%s', hmm_id, hmm_description) + + cds.setdefault('expert', []) + cds['expert'].append(hit) + log.debug( + 'hit: source=UserHMMs, rank=99, contig=%s, start=%i, stop=%i, strand=%s, query-cov=%0.3f, model-cov=%0.3f, hmm-id=%s, gene=%s, product=%s, evalue=%1.1e, bitscore=%f', + cds['contig'], cds['start'], cds['stop'], cds['strand'], hit['aa_cov'], hit['hmm_cov'], hmm_id, hit['gene'], hit['product'], hit['evalue'], hit['score'] + ) + cds_found.add(aa_identifier) + + log.info('found=%i', len(cds_found)) + return cds_found diff --git a/bakta/expert/protein_sequences.py b/bakta/expert/protein_sequences.py index fddc01bc..963df034 100644 --- a/bakta/expert/protein_sequences.py +++ b/bakta/expert/protein_sequences.py @@ -117,7 +117,7 @@ def write_user_protein_sequences(aa_fasta_path: Path): with aa_fasta_path.open('w') as fh_out: for user_protein in user_proteins: (model_id, min_id, min_query_cov, min_model_cov, gene, product, dbxrefs, seq) = user_protein - fh_out.write(f">{model_id} UserProteins~~~{100}~~~{min_id}~~~{min_query_cov}~~~{min_model_cov}~~~{gene}~~~{product}~~~{','.join(dbxrefs)}\n{seq}\n") + fh_out.write(f">{model_id} UserProteins~~~{101}~~~{min_id}~~~{min_query_cov}~~~{min_model_cov}~~~{gene}~~~{product}~~~{','.join(dbxrefs)}\n{seq}\n") log.debug( 'imported user aa: id=%s, length=%i, min-id=%f, min-query-cov=%f, min-model-cov=%f, gene=%s, product=%s, dbxrefs=%s', model_id, len(seq), min_id, min_query_cov, min_model_cov, gene, product, dbxrefs diff --git a/bakta/features/annotation.py b/bakta/features/annotation.py index c139d25c..88841843 100644 --- a/bakta/features/annotation.py +++ b/bakta/features/annotation.py @@ -101,18 +101,17 @@ def combine_annotation(feature: dict): product = ips_product for db_xref in ips['db_xrefs']: db_xrefs.add(db_xref) - rank = 0 - for hit in expert_hits: - db_xrefs.update(hit.get('db_xrefs', [])) - expert_rank = hit['rank'] - if(expert_rank > rank): - expert_genes = hit.get('gene', None) - if(expert_genes): - expert_genes = expert_genes.replace('/', ',').split(',') - genes.update(expert_genes) - gene = expert_genes[0] - product = hit.get('product', None) - rank = expert_rank + + if(len(expert_hits) > 0): + top_expert_hit = sorted(expert_hits,key=lambda k: (k['rank'], k.get('score', 0), calc_annotation_score(k)), reverse=True)[0] + expert_genes = top_expert_hit.get('gene', None) + if(expert_genes): + expert_genes = expert_genes.replace('/', ',').split(',') + genes.update(expert_genes) + gene = expert_genes[0] + product = top_expert_hit.get('product', None) + for hit in expert_hits: + db_xrefs.update(hit.get('db_xrefs', [])) if(product): product = revise_cds_product(product) @@ -404,8 +403,8 @@ def detect_feature_overlaps(genome: dict): elif(sorf['start'] == overlap_sorf['start'] and sorf['stop'] == overlap_sorf['stop']): continue # same else: # overlap -> remove sorf - score_sorf = calc_sorf_annotation_score(sorf) - score_overlap_sorf = calc_sorf_annotation_score(overlap_sorf) + score_sorf = calc_cds_annotation_score(sorf) + score_overlap_sorf = calc_cds_annotation_score(overlap_sorf) if(score_sorf < score_overlap_sorf): # lower annotation score overlap = f"[{max(sorf['start'], overlap_sorf['start'])},{min(sorf['stop'], overlap_sorf['stop'])}]" @@ -431,39 +430,38 @@ def detect_feature_overlaps(genome: dict): ) -def calc_sorf_annotation_score(sorf: dict) -> int: +def calc_cds_annotation_score(cds: dict) -> int: """Calc an annotation score rewarding each identification & annotation""" score = 0 - if('ups' in sorf): + if('ups' in cds): score += 1 - ips = sorf.get('ips', None) + ips = cds.get('ips', None) if(ips): score += 1 - ips_gene = ips.get('gene', None) - if(ips_gene): - score += 1 - ips_product = ips.get('product', None) - if(ips_product): - score += 1 + score += calc_annotation_score(ips) - psc = sorf.get('psc', None) + psc = cds.get('psc', None) if(psc): score += 1 - psc_gene = psc.get('gene', None) - if(psc_gene): - score += 1 - psc_product = psc.get('product', None) - if(psc_product): - score += 1 + score += calc_annotation_score(psc) log.debug( - 'sorf score: contig=%s, start=%i, stop=%i, gene=%s, product=%s, score=%i', - sorf['contig'], sorf['start'], sorf['stop'], sorf.get('gene', '-'), sorf.get('product', '-'), score + 'cds score: contig=%s, start=%i, stop=%i, gene=%s, product=%s, score=%i', + cds['contig'], cds['start'], cds['stop'], cds.get('gene', '-'), cds.get('product', '-'), score ) return score +def calc_annotation_score(orf:dict) -> int: + score = 0 + if(orf.get('gene', None)): + score += 1 + if(orf.get('product', None)): + score += 1 + return score + + def extract_protein_gene_symbol(product: str) -> str: gene_symbols = [] for part in product.split(' '): # try to extract valid gene symbols diff --git a/bakta/features/orf.py b/bakta/features/orf.py index f36a22cb..0d09a6cc 100644 --- a/bakta/features/orf.py +++ b/bakta/features/orf.py @@ -24,7 +24,7 @@ def detect_spurious(orfs: Sequence[dict]): for top_hits in pyhmmer.hmmsearch(hmm, proteins, bit_cutoffs='gathering', cpus=cfg.threads): for hit in top_hits: orf = orf_by_aa_digest[hit.name.decode()] - if hit.evalue > 1E-5: + if hit.evalue > bc.MIN_HMM_EVALUE: log.debug( 'discard low spurious E value: contig=%s, start=%i, stop=%i, strand=%s, subject=%s, evalue=%1.1e, bitscore=%f', orf['contig'], orf['start'], orf['stop'], orf['strand'], hit.best_domain.alignment.hmm_name.decode(), hit.evalue, hit.score diff --git a/bakta/main.py b/bakta/main.py index 01f299b3..c2cbbb2b 100755 --- a/bakta/main.py +++ b/bakta/main.py @@ -15,6 +15,7 @@ import bakta.io.insdc as insdc import bakta.expert.amrfinder as exp_amr import bakta.expert.protein_sequences as exp_aa_seq +import bakta.expert.protein_hmms as exp_aa_hmms import bakta.features.annotation as anno import bakta.features.t_rna as t_rna import bakta.features.tm_rna as tm_rna @@ -62,9 +63,10 @@ def main(): print(f'\tinput: {cfg.genome_path}') print(f"\tdb: {cfg.db_path}, version {cfg.db_info['major']}.{cfg.db_info['minor']}, {cfg.db_info['type']}") if(cfg.replicons): print(f'\treplicon table: {cfg.replicons}') - if(cfg.regions): print(f'\tregion table: {cfg.regions}') if(cfg.prodigal_tf): print(f'\tprodigal training file: {cfg.prodigal_tf}') + if(cfg.regions): print(f'\tregion table: {cfg.regions}') if(cfg.user_proteins): print(f'\tuser proteins: {cfg.user_proteins}') + if(cfg.user_hmms): print(f'\tuser hmms: {cfg.user_hmms}') print(f'\toutput: {cfg.output_path}') if(cfg.force): print(f'\tforce: {cfg.force}') print(f'\ttmp directory: {cfg.tmp_path}') @@ -292,6 +294,11 @@ def main(): user_aa_found = exp_aa_seq.search(cdss, cds_aa_path, 'user_proteins', user_aa_path) print(f'\t\tuser protein sequences: {len(user_aa_found)}') + if(cfg.user_hmms): + log.debug('conduct expert system: user HMM') + user_hmm_found = exp_aa_hmms.search(cdss, cfg.user_hmms) + print(f'\t\tuser HMM sequences: {len(user_hmm_found)}') + if(cfg.gram != bc.GRAM_UNKNOWN): sig_peptides_found = sig_peptides.search(cdss, cds_aa_path) print(f'\tsignal peptides: {len(sig_peptides_found)}') @@ -366,8 +373,8 @@ def main(): if(len(sorfs_not_found) > 0): if(cfg.db_info['type'] == 'full'): log.debug('search sORF PSC') - sorf_pscs, sorfs_not_found = s_orf.search_pscs(sorfs_not_found) - sorf_pscs_psccs.extend(sorf_pscs) + cdss_not_found_tmp, sorfs_not_found = s_orf.search_pscs(sorfs_not_found) + sorf_pscs_psccs.extend(cdss_not_found_tmp) print(f'\tfound PSCs: {len(sorf_pscs_psccs)}') else: log.debug('search sORF PSCC') diff --git a/bakta/proteins.py b/bakta/proteins.py index a3b51158..c413f757 100644 --- a/bakta/proteins.py +++ b/bakta/proteins.py @@ -14,6 +14,7 @@ import bakta.utils as bu import bakta.expert.amrfinder as exp_amr import bakta.expert.protein_sequences as exp_aa_seq +import bakta.expert.protein_hmms as exp_aa_hmms import bakta.features.annotation as anno import bakta.features.orf as orf import bakta.features.cds as feat_cds @@ -42,6 +43,7 @@ def main(): arg_group_annotation = parser.add_argument_group('Annotation') arg_group_annotation.add_argument('--proteins', action='store', default=None, dest='proteins', help='Fasta file of trusted protein sequences for annotation') + arg_group_annotation.add_argument('--hmms', action='store', default=None, dest='hmms', help='HMM file of trusted hidden markov models in HMMER format for CDS annotation') arg_group_general = parser.add_argument_group('General') arg_group_general.add_argument('--help', '-h', action='help', help='Show this help message and exit') @@ -91,6 +93,18 @@ def main(): log.info('debug=%s', cfg.debug) cfg.verbose = True if cfg.debug else args.verbose log.info('verbose=%s', cfg.verbose) + cfg.user_proteins = cfg.check_user_proteins(args) + if(args.hmms is not None): + try: + if(args.hmms == ''): + raise ValueError('File path argument must be non-empty') + user_hmms_path = Path(args.hmms).resolve() + cfg.check_readability('HMM', user_hmms_path) + cfg.check_content_size('HMM', user_hmms_path) + cfg.user_hmms = user_hmms_path + except: + log.error('provided HMM file not valid! path=%s', args.hmms) + sys.exit(f'ERROR: HMM file ({args.hmms}) not valid!') bu.test_dependencies() if(cfg.verbose): @@ -124,7 +138,7 @@ def main(): aa['type'] = bc.FEATURE_CDS aa['aa'] = aa['sequence'] aa['locus'] = aa['id'] - aa['contig'] = 'mock' + aa['contig'] = '-' aa['start'] = mock_start aa['stop'] = -1 aa['strand'] = bc.STRAND_UNKNOWN @@ -132,14 +146,6 @@ def main(): mock_start += 100 print('annotate protein sequences...') annotate_aa(aas) - - for aa in aas: # cleanup mock attributes - aa.pop('contig', None) - aa.pop('start', None) - aa.pop('stop', None) - aa.pop('strand', None) - aa.pop('frame', None) - cfg.run_end = datetime.now() run_duration = (cfg.run_end - cfg.run_start).total_seconds() @@ -149,12 +155,25 @@ def main(): # - write optional output files in TSV, FAA formats # - remove temp directory ############################################################################ - + for aa in aas: # reset mock attributes + aa['start'] = -1 + aa['stop'] = -1 print('write results...') annotations_path = output_path.joinpath(f'{cfg.prefix}.tsv') header_columns = ['ID', 'Length', 'Gene', 'Product', 'EC', 'GO', 'COG', 'RefSeq', 'UniParc', 'UniRef'] print(f'\tfull annotations (TSV): {annotations_path}') tsv.write_protein_features(aas, header_columns, map_aa_columns, annotations_path) + inference_path = output_path.joinpath(f'{cfg.prefix}.inference.tsv') + print(f'\tfeature inferences (TSV): {inference_path}') + mock_contigs = [{'id': '-'}] + features_by_contig = {'-': aas} + tsv.write_feature_inferences(mock_contigs, features_by_contig, inference_path) + for aa in aas: # cleanup mock attributes + aa.pop('contig', None) + aa.pop('start', None) + aa.pop('stop', None) + aa.pop('strand', None) + aa.pop('frame', None) full_annotations_path = output_path.joinpath(f'{cfg.prefix}.json') print(f'\tfull annotations (JSON): {full_annotations_path}') json.write_json(None, aas, full_annotations_path) @@ -233,6 +252,10 @@ def annotate_aa(aas: Sequence[dict]): exp_aa_seq.write_user_protein_sequences(user_aa_path) user_aa_found = exp_aa_seq.search(aas, aa_path, 'user_proteins', user_aa_path) print(f'\t\tuser protein sequences: {len(user_aa_found)}') + if(cfg.user_hmms): + log.debug('conduct expert system: user HMM') + user_hmm_found = exp_aa_hmms.search(aas, cfg.user_hmms) + print(f'\t\tuser HMM sequences: {len(user_hmm_found)}') print('\tcombine annotations and mark hypotheticals...') log.debug('combine CDS annotations') for aa in aas: diff --git a/bakta/utils.py b/bakta/utils.py index 46bae8fe..785da396 100644 --- a/bakta/utils.py +++ b/bakta/utils.py @@ -92,6 +92,7 @@ def parse_arguments(): arg_group_annotation.add_argument('--replicons', '-r', action='store', default=None, dest='replicons', help='Replicon information table (tsv/csv)') arg_group_annotation.add_argument('--regions', action='store', default=None, help='Path to pre-annotated regions in GFF3 or Genbank format (regions only, no functional annotations).') arg_group_annotation.add_argument('--proteins', action='store', default=None, dest='proteins', help='Fasta file of trusted protein sequences for CDS annotation') + arg_group_annotation.add_argument('--hmms', action='store', default=None, dest='hmms', help='HMM file of trusted hidden markov models in HMMER format for CDS annotation') arg_group_annotation.add_argument('--meta', action='store_true', help='Run in metagenome mode. This only affects CDS prediction.') arg_group_workflow = parser.add_argument_group('Workflow') diff --git a/environment.yml b/environment.yml index 0da15485..46f328f9 100644 --- a/environment.yml +++ b/environment.yml @@ -14,7 +14,7 @@ dependencies: - aragorn>=1.2.41 - infernal>=1.1.4 - piler-cr - - pyhmmer>=0.10.4 + - pyhmmer>=0.10.15 - diamond==2.1.8 - blast>=2.14.0 - ncbi-amrfinderplus>=3.11.26 diff --git a/setup.py b/setup.py index bd9f5481..aa0abbd9 100644 --- a/setup.py +++ b/setup.py @@ -32,7 +32,7 @@ 'alive-progress >= 3.0.1', 'PyYAML >= 6.0', 'pyrodigal >= 3.1.0', - 'pyhmmer >= 0.10.4' + 'pyhmmer >= 0.10.15' ], entry_points={ 'console_scripts': [ diff --git a/test/data/NF000185.2.HMM b/test/data/NF000185.2.HMM new file mode 100644 index 00000000..a6d8d07b --- /dev/null +++ b/test/data/NF000185.2.HMM @@ -0,0 +1,2316 @@ +HMMER3/f [3.1b2 | February 2015] +NAME BlaEC +ACC NF000185.1 +DESC NCBIFAM: BlaEC family class C beta-lactamase +LENG 377 +ALPH amino +RF no +MM no +CONS yes +CS no +MAP yes +DATE Tue Aug 27 12:36:06 2019 +NSEQ 10 +EFFN 0.395508 +CKSUM 2497064882 +GA 850 850 +TC 850 850 +NC 750 750 +STATS LOCAL MSV -11.2521 0.69956 +STATS LOCAL VITERBI -12.4431 0.69956 +STATS LOCAL FORWARD -5.8197 0.69956 +HMM A C D E F G H I K L M N P Q R S T V W Y + m->m m->i m->d i->m i->i d->m d->d + COMPO 2.41209 4.33506 3.04628 2.87324 3.31941 2.70889 3.85702 2.77744 2.76760 2.43608 3.70783 3.12524 3.11488 3.09890 3.07189 2.69485 2.79946 2.61865 4.05040 3.38712 + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.00000 * + 1 2.90739 4.47013 3.96211 3.55124 3.17646 3.77266 4.30552 2.34405 3.32305 1.78541 1.54528 3.83830 4.23451 3.71145 3.53765 3.24703 3.21198 2.34011 5.00517 3.75855 1 m - 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- - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 5 2.37253 4.21665 3.35891 3.10979 3.89986 3.05793 4.13288 3.01714 3.05109 2.88342 3.94119 3.33087 3.75604 3.45066 3.31239 2.57313 1.31946 2.72096 5.34509 4.11716 5 t - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 6 3.06499 4.55292 4.05625 3.69808 3.10822 3.87549 4.37965 2.31070 3.46653 0.98368 3.16114 3.98122 4.32660 3.85467 3.65512 3.44008 3.36392 2.32622 4.95535 3.65896 6 l - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 7 2.49977 1.12381 3.99662 3.71922 3.73155 3.13811 4.38463 2.86361 3.54623 2.78188 3.90143 3.72816 3.83854 3.89599 3.68446 2.77089 2.95995 2.61330 5.16285 4.01922 7 c - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 8 1.40868 4.08888 3.38785 3.10302 4.00459 2.94258 4.13447 3.05670 3.08910 2.97815 3.94074 3.26882 3.66739 3.42716 3.37216 2.40342 2.27129 2.69832 5.44561 4.22724 8 a - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 9 3.06499 4.55292 4.05625 3.69808 3.10822 3.87549 4.37965 2.31070 3.46653 0.98368 3.16114 3.98122 4.32660 3.85467 3.65512 3.44008 3.36392 2.32622 4.95535 3.65896 9 l - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 10 3.06499 4.55292 4.05625 3.69808 3.10822 3.87549 4.37965 2.31070 3.46653 0.98368 3.16114 3.98122 4.32660 3.85467 3.65512 3.44008 3.36392 2.32622 4.95535 3.65896 10 l - 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- - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 14 2.27843 4.19650 3.13862 2.95281 3.99538 2.92807 4.06386 3.50788 3.02088 3.23537 4.17001 3.18940 3.66057 3.37723 3.30794 1.22218 2.75281 3.06115 5.37502 4.07899 14 s - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 15 2.49977 1.12381 3.99662 3.71922 3.73155 3.13811 4.38463 2.86361 3.54623 2.78188 3.90143 3.72816 3.83854 3.89599 3.68446 2.77089 2.95995 2.61330 5.16285 4.01922 15 c - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 16 2.27843 4.19650 3.13862 2.95281 3.99538 2.92807 4.06386 3.50788 3.02088 3.23537 4.17001 3.18940 3.66057 3.37723 3.30794 1.22218 2.75281 3.06115 5.37502 4.07899 16 s - 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- - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 20 1.13921 4.15499 3.38209 3.17212 3.97315 2.98118 4.20347 3.08672 3.18629 2.97176 4.01471 3.34159 3.71286 3.53562 3.44111 2.50703 2.77880 2.75557 5.40869 4.20023 20 a - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 21 2.64969 4.41823 3.24841 3.07741 4.07558 3.11050 4.15995 3.60180 3.12801 3.23687 4.28481 3.39129 0.99567 3.51942 3.38105 2.81514 3.08533 3.25638 5.28279 4.19589 21 p - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 22 2.81998 4.79889 2.85340 2.60938 3.95578 3.31407 3.76609 3.57614 2.43658 3.08648 4.11916 3.06743 3.86795 1.38807 2.72135 2.87239 3.11820 3.31172 5.24374 3.93271 22 q - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 23 2.79830 4.92020 2.77401 2.46738 4.18622 3.35855 3.63107 3.65925 2.08029 3.19853 4.11253 2.94784 3.85375 1.72414 2.48208 2.81121 3.04690 3.35320 5.35520 4.05263 23 q - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 24 2.96719 4.41178 4.21419 3.82875 3.32118 3.97377 4.57362 1.18616 3.65507 1.92685 3.27216 4.08569 4.41496 4.01325 3.86117 3.46301 3.26874 1.85068 5.19331 3.92289 24 i - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 25 2.65880 4.64894 2.66979 2.54810 3.99987 3.13150 3.86086 3.69464 2.75885 3.35163 4.30910 1.31252 3.78039 3.13534 3.10908 2.73035 3.03910 3.32520 5.31562 3.95554 25 n - 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- - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 374 2.65880 4.64894 2.66979 2.54810 3.99987 3.13150 3.86086 3.69464 2.75885 3.35163 4.30910 1.31252 3.78039 3.13534 3.10908 2.73035 3.03910 3.32520 5.31562 3.95554 374 n - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 375 1.13921 4.15499 3.38209 3.17212 3.97315 2.98118 4.20347 3.08672 3.18629 2.97176 4.01471 3.34159 3.71286 3.53562 3.44111 2.50703 2.77880 2.75557 5.40869 4.20023 375 a - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 376 3.06499 4.55292 4.05625 3.69808 3.10822 3.87549 4.37965 2.31070 3.46653 0.98368 3.16114 3.98122 4.32660 3.85467 3.65512 3.44008 3.36392 2.32622 4.95535 3.65896 376 l - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.03413 3.79031 4.51266 0.61958 0.77255 0.48576 0.95510 + 377 2.81998 4.79889 2.85340 2.60938 3.95578 3.31407 3.76609 3.57614 2.43658 3.08648 4.11916 3.06743 3.86795 1.38807 2.72135 2.87239 3.11820 3.31172 5.24374 3.93271 377 q - - - + 2.68618 4.42225 2.77519 2.73123 3.46354 2.40513 3.72494 3.29354 2.67741 2.69355 4.24690 2.90347 2.73739 3.18146 2.89801 2.37887 2.77519 2.98518 4.58477 3.61503 + 0.02310 3.77928 * 0.61958 0.77255 0.00000 * +// diff --git a/test/test_args.py b/test/test_args.py index 0aa14116..2e175377 100644 --- a/test/test_args.py +++ b/test/test_args.py @@ -282,6 +282,27 @@ def test_proteins_failiing(parameters, tmpdir): assert proc.returncode != 0 +@pytest.mark.parametrize( + 'parameters', + [ + (['--hmms']), # not provided + (['--hmms', '']), # empty + (['--hmms', 'foo']), # not existing + (['--hmms', 'test/data/empty']), # empty file + (['--hmms', 'test/data/nonsense.txt']) # nonsense file + ] +) +def test_hmms_failiing(parameters, tmpdir): + # test HMM file arguments + proc = run( + ['bin/bakta', '--db', 'test/db', '--output', tmpdir, '--force'] + + parameters + + ['--skip-tmrna', '--skip-trna', '--skip-rrna', '--skip-ncrna', '--skip-ncrna-region', '--skip-crispr', '--skip-sorf', '--skip-ori', '--skip-gap', '--skip-plot'] + + ['test/data/NC_002127.1.fna'] + ) + assert proc.returncode != 0 + + @pytest.mark.parametrize( 'parameters', [ diff --git a/test/test_bakta.py b/test/test_bakta.py index e7d6bdb5..d4c4f261 100644 --- a/test/test_bakta.py +++ b/test/test_bakta.py @@ -109,6 +109,7 @@ def test_bakta_genome(db, tmpdir): '--replicons', 'test/data/replicons.tsv', '--regions', 'test/data/NC_002127.1-region.gff3', '--proteins', 'test/data/user-proteins.faa', + '--hmms', 'test/data/NF000185.2.HMM', '--compliant', 'test/data/GCF_000008865.2.fna.gz'] )