genome-minimal-fail.gff

##gff-version 3
scaffold_28	prediction	gene	1	402	0	+	.	ID=545184;Name=545184
scaffold_28	prediction	gene	805	981	0	-	.	ID=93782;Name=93782
scaffold_28	prediction	gene	2030	2721	0	+	.	ID=545205;Name=545205
scaffold_28	prediction	gene	3273	3545	0	-	.	Name=YOL159C-A;Synteny=no_synteny;SystematicGeneName=YOL159C-A;ID=38792
scaffold_28	prediction	gene	5318	5833	0	-	.	Name=YOL159C;Synteny=no_synteny;SystematicGeneName=YOL159C;ID=38793
scaffold_28	prediction	gene	6780	8600	0	-	.	Name=ENB1;Synteny=no_synteny;SystematicGeneName=YOL158C;StandardGeneName=ENB1;ID=38794
scaffold_28	prediction	gene	9698	11467	0	-	.	Name=IMA4;Synteny=no_synteny;SystematicGeneName=YJL221C;StandardGeneName=IMA4;ID=38795

minimal-fail.py

import gffutils
import os

def updateGenome():
    genomeGFF="genome-minimal-fail.gff"
    genomeGFFdb = genomeGFF.replace(".gff", ".db")

    #create database for genome
    if os.path.isfile(genomeGFFdb):
        db = gffutils.FeatureDB(genomeGFFdb)
    else:
        db = gffutils.create_db(genomeGFF, dbfn=genomeGFFdb, force=True, merge_strategy="merge")

    #shift coordinates of features that follow the original integration site by deletion size
    downstreamGenomeFeatures = db.region('scaffold_28:6001-11467', completely_within=True)

    def gen():
        for feature in downstreamGenomeFeatures:
            print(feature["Name"][0])
            feature.start += 10000
            feature.end += 10000
            print(feature.end)
        yield feature

    db.update(gen(), merge_strategy="replace")

    return

updateGenome()