# HG changeset patch # User cpt_testbed # Date 1651231950 0 # Node ID d8752390c7f789a2dafed2ed7e7b58e31ee37662 Uploaded diff -r 000000000000 -r d8752390c7f7 cpt-macros.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/cpt-macros.xml Fri Apr 29 11:32:30 2022 +0000 @@ -0,0 +1,115 @@ + + + + + python + biopython + requests + + + + + + + + 10.1371/journal.pcbi.1008214 + @unpublished{galaxyTools, + author = {E. Mijalis, H. Rasche}, + title = {CPT Galaxy Tools}, + year = {2013-2017}, + note = {https://github.com/tamu-cpt/galaxy-tools/} + } + + + + + 10.1371/journal.pcbi.1008214 + + @unpublished{galaxyTools, + author = {E. Mijalis, H. Rasche}, + title = {CPT Galaxy Tools}, + year = {2013-2017}, + note = {https://github.com/tamu-cpt/galaxy-tools/} + } + + + + + + + 10.1371/journal.pcbi.1008214 + + @unpublished{galaxyTools, + author = {C. Ross}, + title = {CPT Galaxy Tools}, + year = {2020-}, + note = {https://github.com/tamu-cpt/galaxy-tools/} + } + + + + + + + 10.1371/journal.pcbi.1008214 + + @unpublished{galaxyTools, + author = {E. Mijalis, H. Rasche}, + title = {CPT Galaxy Tools}, + year = {2013-2017}, + note = {https://github.com/tamu-cpt/galaxy-tools/} + } + + + @unpublished{galaxyTools, + author = {A. Criscione}, + title = {CPT Galaxy Tools}, + year = {2019-2021}, + note = {https://github.com/tamu-cpt/galaxy-tools/} + } + + + + + + + 10.1371/journal.pcbi.1008214 + + @unpublished{galaxyTools, + author = {A. Criscione}, + title = {CPT Galaxy Tools}, + year = {2019-2021}, + note = {https://github.com/tamu-cpt/galaxy-tools/} + } + + + + + + + 10.1371/journal.pcbi.1008214 + + @unpublished{galaxyTools, + author = {C. Maughmer}, + title = {CPT Galaxy Tools}, + year = {2017-2020}, + note = {https://github.com/tamu-cpt/galaxy-tools/} + } + + + + + + + @unpublished{galaxyTools, + author = {C. Maughmer}, + title = {CPT Galaxy Tools}, + year = {2017-2020}, + note = {https://github.com/tamu-cpt/galaxy-tools/} + } + + + + diff -r 000000000000 -r d8752390c7f7 fix-aragorn-gff3.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/fix-aragorn-gff3.py Fri Apr 29 11:32:30 2022 +0000 @@ -0,0 +1,65 @@ +#!/usr/bin/env python +import sys +import logging +import argparse +from CPT_GFFParser import gffParse, gffWrite, gffSeqFeature +from Bio.SeqFeature import SeqFeature +from gff3 import feature_lambda, feature_test_type + +logging.basicConfig(level=logging.INFO) +log = logging.getLogger(__name__) + + +def fixed_feature(rec): + for idx, feature in enumerate( + feature_lambda( + rec.features, feature_test_type, {"types": ["tRNA", "tmRNA"]}, subfeatures=True + ) + ): + + fid = "%s-%03d" % (feature.type, 1 + idx) + try: + name = [feature.type + "-" + feature.qualifiers["Codon"][0]] + except KeyError: + name = [feature.qualifiers['product'][0]] + try: + origSource = feature.qualifiers["source"][0] + except: + origSource = "." + gene = gffSeqFeature( + location=feature.location, + type="gene", + qualifiers={"ID": [fid + ".gene"], "source": [origSource], "Name": name}, + ) + feature.qualifiers["Name"] = name + # Below that we have an mRNA + exon = gffSeqFeature( + location=feature.location, + type="exon", + qualifiers={"source": [origSource], "ID": ["%s.exon" % fid], "Name": name}, + ) + feature.qualifiers["ID"] = [fid] + exon.qualifiers["Parent"] = [fid] + feature.qualifiers["Parent"] = [fid + ".gene"] + # gene -> trna -> exon + feature.sub_features = [exon] + gene.sub_features = [feature] + yield gene + + +def gff_filter(gff3): + found_gff = False + for rec in gffParse(gff3): + found_gff = True + rec.features = sorted(list(fixed_feature(rec)), key=lambda x: x.location.start) + rec.annotations = {} + gffWrite([rec], sys.stdout) + if not found_gff: + print("##gff-version 3") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="add parent gene features to CDSs") + parser.add_argument("gff3", type=argparse.FileType("r"), help="GFF3 annotations") + args = parser.parse_args() + gff_filter(**vars(args)) diff -r 000000000000 -r d8752390c7f7 fix-aragorn-gff3.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/fix-aragorn-gff3.xml Fri Apr 29 11:32:30 2022 +0000 @@ -0,0 +1,33 @@ + + + + + macros.xml + cpt-macros.xml + + + $default]]> + + + + + + + + + + + + + + + diff -r 000000000000 -r d8752390c7f7 gff3.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/gff3.py Fri Apr 29 11:32:30 2022 +0000 @@ -0,0 +1,346 @@ +import copy +import logging + +log = logging.getLogger() +log.setLevel(logging.WARN) + + +def feature_lambda( + feature_list, + test, + test_kwargs, + subfeatures=True, + parent=None, + invert=False, + recurse=True, +): + """Recursively search through features, testing each with a test function, yielding matches. + + GFF3 is a hierachical data structure, so we need to be able to recursively + search through features. E.g. if you're looking for a feature with + ID='bob.42', you can't just do a simple list comprehension with a test + case. You don't know how deeply burried bob.42 will be in the feature tree. This is where feature_lambda steps in. + + :type feature_list: list + :param feature_list: an iterable of features + + :type test: function reference + :param test: a closure with the method signature (feature, **kwargs) where + the kwargs are those passed in the next argument. This + function should return True or False, True if the feature is + to be yielded as part of the main feature_lambda function, or + False if it is to be ignored. This function CAN mutate the + features passed to it (think "apply"). + + :type test_kwargs: dictionary + :param test_kwargs: kwargs to pass to your closure when it is called. + + :type subfeatures: boolean + :param subfeatures: when a feature is matched, should just that feature be + yielded to the caller, or should the entire sub_feature + tree for that feature be included? subfeatures=True is + useful in cases such as searching for a gene feature, + and wanting to know what RBS/Shine_Dalgarno_sequences + are in the sub_feature tree (which can be accomplished + with two feature_lambda calls). subfeatures=False is + useful in cases when you want to process (and possibly + return) the entire feature tree, such as applying a + qualifier to every single feature. + + :type invert: boolean + :param invert: Negate/invert the result of the filter. + + :rtype: yielded list + :return: Yields a list of matching features. + """ + # Either the top level set of [features] or the subfeature attribute + for feature in feature_list: + feature._parent = parent + if not parent: + # Set to self so we cannot go above root. + feature._parent = feature + test_result = test(feature, **test_kwargs) + # if (not invert and test_result) or (invert and not test_result): + if invert ^ test_result: + if not subfeatures: + feature_copy = copy.deepcopy(feature) + feature_copy.sub_features = list() + yield feature_copy + else: + yield feature + + if recurse and hasattr(feature, "sub_features"): + for x in feature_lambda( + feature.sub_features, + test, + test_kwargs, + subfeatures=subfeatures, + parent=feature, + invert=invert, + recurse=recurse, + ): + yield x + + +def fetchParent(feature): + if not hasattr(feature, "_parent") or feature._parent is None: + return feature + else: + return fetchParent(feature._parent) + + +def feature_test_true(feature, **kwargs): + return True + + +def feature_test_type(feature, **kwargs): + if "type" in kwargs: + return str(feature.type).upper() == str(kwargs["type"]).upper() + elif "types" in kwargs: + for x in kwargs["types"]: + if str(feature.type).upper() == str(x).upper(): + return True + return False + raise Exception("Incorrect feature_test_type call, need type or types") + + +def feature_test_qual_value(feature, **kwargs): + """Test qualifier values. + + For every feature, check that at least one value in + feature.quailfiers(kwargs['qualifier']) is in kwargs['attribute_list'] + """ + if isinstance(kwargs["qualifier"], list): + for qualifier in kwargs["qualifier"]: + for attribute_value in feature.qualifiers.get(qualifier, []): + if attribute_value in kwargs["attribute_list"]: + return True + else: + for attribute_value in feature.qualifiers.get(kwargs["qualifier"], []): + if attribute_value in kwargs["attribute_list"]: + return True + return False + + +def feature_test_location(feature, **kwargs): + if "strand" in kwargs: + if feature.location.strand != kwargs["strand"]: + return False + + return feature.location.start <= kwargs["loc"] <= feature.location.end + + +def feature_test_quals(feature, **kwargs): + """ + Example:: + + a = Feature(qualifiers={'Note': ['Some notes', 'Aasdf']}) + + # Check if a contains a Note + feature_test_quals(a, {'Note': None}) # Returns True + feature_test_quals(a, {'Product': None}) # Returns False + + # Check if a contains a note with specific value + feature_test_quals(a, {'Note': ['ome']}) # Returns True + + # Check if a contains a note with specific value + feature_test_quals(a, {'Note': ['other']}) # Returns False + """ + for key in kwargs: + if key not in feature.qualifiers: + return False + + # Key is present, no value specified + if kwargs[key] is None: + return True + + # Otherwise there is a key value we're looking for. + # so we make a list of matches + matches = [] + # And check all of the feature qualifier valuse + for value in feature.qualifiers[key]: + # For that kwargs[key] value + for x in kwargs[key]: + matches.append(x in value) + + # If none matched, then we return false. + if not any(matches): + return False + + return True + + +def feature_test_contains(feature, **kwargs): + if "index" in kwargs: + return feature.location.start < kwargs["index"] < feature.location.end + elif "range" in kwargs: + return ( + feature.location.start < kwargs["range"]["start"] < feature.location.end + and feature.location.start < kwargs["range"]["end"] < feature.location.end + ) + else: + raise RuntimeError("Must use index or range keyword") + + +def get_id(feature=None, parent_prefix=None): + result = "" + if parent_prefix is not None: + result += parent_prefix + "|" + if "locus_tag" in feature.qualifiers: + result += feature.qualifiers["locus_tag"][0] + elif "gene" in feature.qualifiers: + result += feature.qualifiers["gene"][0] + elif "Gene" in feature.qualifiers: + result += feature.qualifiers["Gene"][0] + elif "product" in feature.qualifiers: + result += feature.qualifiers["product"][0] + elif "Product" in feature.qualifiers: + result += feature.qualifiers["Product"][0] + elif "Name" in feature.qualifiers: + result += feature.qualifiers["Name"][0] + else: + return feature.id + # Leaving in case bad things happen. + # result += '%s_%s_%s_%s' % ( + # feature.id, + # feature.location.start, + # feature.location.end, + # feature.location.strand + # ) + return result + + +def get_gff3_id(gene): + return gene.qualifiers.get("Name", [gene.id])[0] + + +def ensure_location_in_bounds(start=0, end=0, parent_length=0): + # This prevents frameshift errors + while start < 0: + start += 3 + while end < 0: + end += 3 + while start > parent_length: + start -= 3 + while end > parent_length: + end -= 3 + return (start, end) + + +def coding_genes(feature_list): + for x in genes(feature_list): + if ( + len( + list( + feature_lambda( + x.sub_features, + feature_test_type, + {"type": "CDS"}, + subfeatures=False, + ) + ) + ) + > 0 + ): + yield x + + +def genes(feature_list, feature_type="gene", sort=False): + """ + Simple filter to extract gene features from the feature set. + """ + + if not sort: + for x in feature_lambda( + feature_list, feature_test_type, {"type": feature_type}, subfeatures=True + ): + yield x + else: + data = list(genes(feature_list, feature_type=feature_type, sort=False)) + data = sorted(data, key=lambda feature: feature.location.start) + for x in data: + yield x + + +def wa_unified_product_name(feature): + """ + Try and figure out a name. We gave conflicting instructions, so + this isn't as trivial as it should be. Sometimes it will be in + 'product' or 'Product', othertimes in 'Name' + """ + # Manually applied tags. + protein_product = feature.qualifiers.get( + "product", feature.qualifiers.get("Product", [None]) + )[0] + + # If neither of those are available ... + if protein_product is None: + # And there's a name... + if "Name" in feature.qualifiers: + if not is_uuid(feature.qualifiers["Name"][0]): + protein_product = feature.qualifiers["Name"][0] + + return protein_product + + +def is_uuid(name): + return name.count("-") == 4 and len(name) == 36 + + +def get_rbs_from(gene): + # Normal RBS annotation types + rbs_rbs = list( + feature_lambda( + gene.sub_features, feature_test_type, {"type": "RBS"}, subfeatures=False + ) + ) + rbs_sds = list( + feature_lambda( + gene.sub_features, + feature_test_type, + {"type": "Shine_Dalgarno_sequence"}, + subfeatures=False, + ) + ) + # Fraking apollo + apollo_exons = list( + feature_lambda( + gene.sub_features, feature_test_type, {"type": "exon"}, subfeatures=False + ) + ) + apollo_exons = [x for x in apollo_exons if len(x) < 10] + # These are more NCBI's style + regulatory_elements = list( + feature_lambda( + gene.sub_features, + feature_test_type, + {"type": "regulatory"}, + subfeatures=False, + ) + ) + rbs_regulatory = list( + feature_lambda( + regulatory_elements, + feature_test_quals, + {"regulatory_class": ["ribosome_binding_site"]}, + subfeatures=False, + ) + ) + # Here's hoping you find just one ;) + return rbs_rbs + rbs_sds + rbs_regulatory + apollo_exons + + +def nice_name(record): + """ + get the real name rather than NCBI IDs and so on. If fails, will return record.id + """ + name = record.id + likely_parental_contig = list(genes(record.features, feature_type="contig")) + if len(likely_parental_contig) == 1: + name = likely_parental_contig[0].qualifiers.get("organism", [name])[0] + return name + + +def fsort(it): + for i in sorted(it, key=lambda x: int(x.location.start)): + yield i diff -r 000000000000 -r d8752390c7f7 macros.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/macros.xml Fri Apr 29 11:32:30 2022 +0000 @@ -0,0 +1,56 @@ + + + + + python + biopython + cpt_gffparser + + + + + + + + + + + + + + + + + + + + + + + + + + + + "$gff3_data" + + +#if str($reference_genome.reference_genome_source) == 'cached': + "${reference_genome.fasta_indexes.fields.path}" +#else if str($reference_genome.reference_genome_source) == 'history': + genomeref.fa +#end if + + +#if $reference_genome.reference_genome_source == 'history': + ln -s $reference_genome.genome_fasta genomeref.fa; +#end if + + +#if str($reference_genome.reference_genome_source) == 'cached': + "${reference_genome.fasta_indexes.fields.path}" +#else if str($reference_genome.reference_genome_source) == 'history': + genomeref.fa +#end if + + diff -r 000000000000 -r d8752390c7f7 test-data/FixAra_In.gff3 --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/FixAra_In.gff3 Fri Apr 29 11:32:30 2022 +0000 @@ -0,0 +1,2 @@ +##gff-version-3 +Phriendly aragorn tRNA 48610 48685 . - . Anticodon="tcc";Codon="Gly" diff -r 000000000000 -r d8752390c7f7 test-data/FixAra_Out.gff3 --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/FixAra_Out.gff3 Fri Apr 29 11:32:30 2022 +0000 @@ -0,0 +1,4 @@ +##gff-version 3 +Phriendly feature gene 48610 48685 . - . ID=tRNA-001.gene;source=.;Name=tRNA-"Gly"; +Phriendly aragorn tRNA 48610 48685 . - . Anticodon="tcc";Codon="Gly";Name=tRNA-"Gly";ID=tRNA-001;Parent=tRNA-001.gene; +Phriendly feature exon 48610 48685 . - . source=.;ID=tRNA-001.exon;Name=tRNA-"Gly";Parent=tRNA-001;