orfipy

orfipy extracts open reading frames (ORFs) from FASTA sequences to identify candidate coding regions in genome and transcriptome assemblies.

Key Features:

• Speed and Efficiency: Implements multi-core processing with Cython-enhanced Python code to provide fast ORF extraction, outperforming OrfM and getorf on numerous small FASTA sequences such as de novo transcriptome assemblies.
• Flexibility and Customization: Provides extensive customizable search criteria for ORF detection, enabling detection of alternative reading frames and tailored coding region annotation.
• Versatile Output Formats: Supports FASTA and BED output formats for integration with downstream analyses.

Scientific Applications:

• Coding region annotation: Extracts ORFs to annotate coding sequences in newly sequenced genomes and transcriptomes.
• Alternative reading frame analysis: Identifies alternative reading frames within known genes to support studies of gene expression regulation and protein diversity.
• High-throughput RNA-Seq processing: Processes large RNA-Seq-derived assemblies efficiently for ORF discovery in high-throughput sequencing datasets.

Methodology:

Implemented in Python with Cython enhancements, orfipy employs multi-core CPU processing and is compatible with Python 3.6 and higher.