--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/gff3_rebase.py	Thu Apr 20 08:12:49 2017 -0400
@@ -0,0 +1,180 @@
+#!/usr/bin/env python
+import argparse
+import copy
+import logging
+import sys
+
+from BCBio import GFF
+from Bio.SeqFeature import FeatureLocation
+
+logging.basicConfig(level=logging.INFO)
+log = logging.getLogger(__name__)
+
+__author__ = "Eric Rasche"
+__version__ = "0.4.0"
+__maintainer__ = "Eric Rasche"
+__email__ = "esr@tamu.edu"
+
+
+def feature_lambda(feature_list, test, test_kwargs, subfeatures=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.
+
+    :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:
+        if test(feature, **test_kwargs):
+            if not subfeatures:
+                feature_copy = copy.deepcopy(feature)
+                feature_copy.sub_features = []
+                yield feature_copy
+            else:
+                yield feature
+
+        if hasattr(feature, 'sub_features'):
+            for x in feature_lambda(feature.sub_features, test, test_kwargs, subfeatures=subfeatures):
+                yield x
+
+
+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']
+    """
+    for attribute_value in feature.qualifiers.get(kwargs['qualifier'], []):
+        if attribute_value in kwargs['attribute_list']:
+            return True
+    return False
+
+
+def __get_features(child, interpro=False):
+    child_features = {}
+    for rec in GFF.parse(child):
+        for feature in rec.features:
+            parent_feature_id = rec.id
+            if interpro:
+                if feature.type == 'polypeptide':
+                    continue
+                if '_' in parent_feature_id:
+                    parent_feature_id = parent_feature_id[parent_feature_id.index('_') + 1:]
+
+            try:
+                child_features[parent_feature_id].append(feature)
+            except KeyError:
+                child_features[parent_feature_id] = [feature]
+    return child_features
+
+
+def __update_feature_location(feature, parent, protein2dna):
+    start = feature.location.start
+    end = feature.location.end
+    if protein2dna:
+        start *= 3
+        end *= 3
+
+    if parent.location.strand >= 0:
+        ns = parent.location.start + start
+        ne = parent.location.start + end
+        st = +1
+    else:
+        ns = parent.location.end - end
+        ne = parent.location.end - start
+        st = -1
+
+    # Don't let start/stops be less than zero. It's technically valid for them
+    # to be (at least in the model I'm working with) but it causes numerous
+    # issues.
+    #
+    # Instead, we'll replace with %3 to try and keep it in the same reading
+    # frame that it should be in.
+    if ns < 0:
+        ns %= 3
+    if ne < 0:
+        ne %= 3
+
+    feature.location = FeatureLocation(ns, ne, strand=st)
+
+    if hasattr(feature, 'sub_features'):
+        for subfeature in feature.sub_features:
+            __update_feature_location(subfeature, parent, protein2dna)
+
+
+def rebase(parent, child, interpro=False, protein2dna=False):
+    child_features = __get_features(child, interpro=interpro)
+
+    for rec in GFF.parse(parent):
+        replacement_features = []
+        for feature in feature_lambda(
+                rec.features,
+                feature_test_qual_value,
+                {
+                    'qualifier': 'ID',
+                    'attribute_list': child_features.keys(),
+                },
+                subfeatures=False):
+
+            new_subfeatures = child_features[feature.id]
+            fixed_subfeatures = []
+            for x in new_subfeatures:
+                # Then update the location of the actual feature
+                __update_feature_location(x, feature, protein2dna)
+
+                if interpro:
+                    for y in ('status', 'Target'):
+                        try:
+                            del x.qualifiers[y]
+                        except:
+                            pass
+
+                fixed_subfeatures.append(x)
+            replacement_features.extend(fixed_subfeatures)
+        # We do this so we don't include the original set of features that we
+        # were rebasing against in our result.
+        rec.features = replacement_features
+        rec.annotations = {}
+        GFF.write([rec], sys.stdout)
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser(description='rebase gff3 features against parent locations', epilog="")
+    parser.add_argument('parent', type=argparse.FileType('r'), help='Parent GFF3 annotations')
+    parser.add_argument('child', type=argparse.FileType('r'), help='Child GFF3 annotations to rebase against parent')
+    parser.add_argument('--interpro', action='store_true',
+                        help='Interpro specific modifications')
+    parser.add_argument('--protein2dna', action='store_true',
+                        help='Map protein translated results to original DNA data')
+    args = parser.parse_args()
+    rebase(**vars(args))