bio-genome-intervals-gtf-gff-handling

Version Compatibility

Reference examples tested with: bedtools 2.31+, pandas 2.2+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

GTF/GFF Handling

"Parse gene annotations from GTF/GFF" → Read gene models, extract features by type (gene, exon, CDS), and query attributes from annotation files.

• Python: gffutils.create_db('file.gtf') (gffutils), pyranges.read_gtf() (pyranges)
• CLI: awk on tab-delimited GTF fields

GTF and GFF3 are standard gene annotation formats. Both use 1-based coordinates.

Format Comparison

Feature	GTF	GFF3
Coordinate system	1-based, inclusive	1-based, inclusive
Hierarchy	Implicit (gene_id, transcript_id)	Explicit (Parent attribute)
Attribute format	key "value";	key=value;
Comments	#	#
Fasta sequences	Not standard	##FASTA directive

GTF Format

chr1	HAVANA	gene	11869	14409	.	+	.	gene_id "ENSG00000223972"; gene_name "DDX11L1";
chr1	HAVANA	transcript	11869	14409	.	+	.	gene_id "ENSG00000223972"; transcript_id "ENST00000456328";
chr1	HAVANA	exon	11869	12227	.	+	.	gene_id "ENSG00000223972"; transcript_id "ENST00000456328"; exon_number "1";

GFF3 Format

chr1	HAVANA	gene	11869	14409	.	+	.	ID=ENSG00000223972;Name=DDX11L1
chr1	HAVANA	mRNA	11869	14409	.	+	.	ID=ENST00000456328;Parent=ENSG00000223972
chr1	HAVANA	exon	11869	12227	.	+	.	ID=exon1;Parent=ENST00000456328

Parse GTF with gtfparse (Python)

Installation

pip install gtfparse

Basic Parsing

import gtfparse

# Load entire GTF
df = gtfparse.read_gtf('annotation.gtf')

# View columns
print(df.columns)
# ['seqname', 'source', 'feature', 'start', 'end', 'score', 'strand', 'frame',
#  'gene_id', 'transcript_id', 'gene_name', ...]

# Filter by feature type
genes = df[df['feature'] == 'gene']
transcripts = df[df['feature'] == 'transcript']
exons = df[df['feature'] == 'exon']

# Get specific gene
gene_df = df[df['gene_name'] == 'TP53']