Question: I have a GFF annotation for my sequences where many protein sub-features are overlapping. I want to extract the longest of those sub-features (i.e. one sub-feature for each sequence).

For example, the following is how my gff file looks:

```
chrA01:14912487-14917603(-)_Name=Name1 Source1 repeat 6 5116 . - . ID=repeat_region1
chrA01:14912487-14917603(-)_Name=Name1 Source1 inverted 6 7 . - . Parent=repeat_region1
chrA01:14912487-14917603(-)_Name=Name1 Source1 LTR 6 5116 . - . ID=LTR_retrotransposon1;Parent=repeat_region1;similarity=95.70;seq_number=666
chrA01:14912487-14917603(-)_Name=Name1 Source1 ltrs 6 302 . - . Parent=LTR_retrotransposon1
chrA01:14912487-14917603(-)_Name=Name1 Source2 protein 535 835 1.7e-16 - . Parent=LTR_retrotransposon1;reading_frame=0;name=INT_crm
chrA01:14912487-14917603(-)_Name=Name1 Source2 protein 535 874 0 - . Parent=LTR_retrotransposon1;reading_frame=0;name=INT_reina
chrA01:14912487-14917603(-)_Name=Name1 Source2 protein 547 772 1.9e-28 - . Parent=LTR_retrotransposon1;reading_frame=0;name=INT_del
chrA01:14912487-14917603(-)_Name=Name1 Source2 protein 1812 2124 8.3e-41 - . Parent=LTR_retrotransposon1;reading_frame=1;name=RNaseH_galadriel
chrA01:14912487-14917603(-)_Name=Name1 Source2 protein 1812 2127 4.6e-15 - . Parent=LTR_retrotransposon1;reading_frame=1;name=RNaseH_v_clade
chrA01:14912487-14917603(-)_Name=Name1 Source2 protein 1812 2127 1.2e-16 - . Parent=LTR_retrotransposon1;reading_frame=1;name=RNaseH_athila
chrA01:14912487-14917603(-)_Name=Name1 Source1 ltrs 4815 5116 . - . Parent=LTR_retrotransposon1
chrA01:14912487-14917603(-)_Name=Name1 Source1 inverted 5115 5116 . - . Parent=repeat_region1
###
chrA01:18337410-18342821(-)_Name=Name2 Source1 repeat 1 5411 . - . ID=repeat_region2
chrA01:18337410-18342821(-)_Name=Name2 Source1 inverted 1 2 . - . Parent=repeat_region2
chrA01:18337410-18342821(-)_Name=Name2 Source1 LTR 1 5411 . - . ID=LTR_retrotransposon2;Parent=repeat_region2;similarity=98.93;seq_number=794
chrA01:18337410-18342821(-)_Name=Name2 Source1 ltrs 1 374 . - . Parent=LTR_retrotransposon2
chrA01:18337410-18342821(-)_Name=Name2 Source2 protein 427 1435 0 - . Parent=LTR_retrotransposon2;reading_frame=1;name=INT_crm
chrA01:18337410-18342821(-)_Name=Name2 Source2 protein 439 1390 1.8e-38 - . Parent=LTR_retrotransposon2;reading_frame=1;name=INT_TF
chrA01:18337410-18342821(-)_Name=Name2 Source2 protein 481 1435 0 - . Parent=LTR_retrotransposon2;reading_frame=1;name=INT_v_clade
chrA01:18337410-18342821(-)_Name=Name2 Source2 protein 1657 1990 3e-18 - . Parent=LTR_retrotransposon2;reading_frame=1;name=RNaseH_v_clade
chrA01:18337410-18342821(-)_Name=Name2 Source2 protein 1657 1990 6.8e-17 - . Parent=LTR_retrotransposon2;reading_frame=1;name=RNaseH_csrn1
chrA01:18337410-18342821(-)_Name=Name2 Source2 protein 1657 1990 2.7e-35 - . Parent=LTR_retrotransposon2;reading_frame=1;name=RNaseH_reina
chrA01:18337410-18342821(-)_Name=Name2 Source1 ltrs 5038 5411 . - . Parent=LTR_retrotransposon2
chrA01:18337410-18342821(-)_Name=Name2 Source1 inverted 5410 5411 . - . Parent=repeat_region2
###
```

I want to extract the longest or the best RNaseH regions from each sequence. I am able to parse the gff to get RNase annotations. But, I am not sure how to proceed next:

```
from gffutils.iterators import DataIterator
from Bio import SeqIO

input_filename = 'mygff.gff'
infasta = list(SeqIO.parse('myseqs.fasta', 'fasta'))
features=DataIterator(input_filename)

for feature in features:
if "name=RNaseH" in str(feature):
print str(feature)
#check lengths
#check e-values
```

Answer: Your question is a little confusing, but I'll try my best, hopefully we'll get somewhere. Firstly I wonder (just of curiosity) how did you come across this `gffutils` tool. GFF is a flat text file. One would usually just write a parser to get relevant info from the file. But this `gffutil` thing is actually pretty cool and since you want to get actual sequences as well, this tool should do it all for you.

Firstly, are you familiar with python `dir` function? It returns a list of valid attributes for that object. e.g `dir("string")` will return all methods available to a "string". You can also use ipython to tab expand methods.This is a good exploratory exercise of new methods, particular for new tools like this one, since little info available online. You can further call `help("string".endswith)` to get info on how to apply particular method.

Do this for your own knowledge:

```
import sys
from gffutils.iterators import DataIterator

myGFF = sys.argv[1]
myFasta = sys.argv[2]

for feature in DataIterator(myGFF):
print dir(feature)
break
```

This should return a list like this:

['__class__', '__delattr__', '__dict__', '__doc__', '__eq__', '__format__', '__getattribute__', '__getitem__', '__hash__', '__init__', '__len__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__setitem__', '__sizeof__', '__str__', '__subclasshook__', '__unicode__', '__weakref__', 'astuple', 'attributes', 'bin', 'calc_bin', 'chrom', 'dialect', 'end', 'extra', 'featuretype', 'file_order', 'frame', 'id', 'keep_order', 'score', 'seqid', 'sequence', 'sort_attribute_values', 'source', 'start', 'stop', 'strand]

Don't worry about things with double underscore! All other things you should experiment with.

I believe this is along the line what you are asking for

```
import sys
from gffutils.iterators import DataIterator

myGFF = sys.argv[1]
myFasta = sys.argv[2]

for feature in DataIterator(myGFF):
if feature.featuretype == "RNaseH":
print feature.seqid, feature.featuretype, len(feature), feature.sequence(myFasta)
```

This will return first column value (usually chromosome name), the feature type (in you case RNaseH), the length of that feature and the most awesome thing in my opinion is this last method `feature.sequence()` which returns the sequence fragment of you requested feature, using coordinates from the gff file. That is really cool I think.

I'm not sure how to help you with "the longest/ the best RHaseH reagion" thing since it something very specific to you, but you should be able to impose some sort of test on `len(feature)` to tease out your sequence of interest.

p.s also have a look at this post https://www.biostars.org/p/138849/