Urminder Singh1,2,3, Eve Syrkin Wurtele1,2,3. 1. Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011. 2. Center for Metabolic Biology, Iowa State University, Ames, IA 50011. 3. Department of Genetics Development and Cell Biology, Iowa State University, Ames, IA 50011.
Abstract
SUMMARY: Searching for open reading frames is a routine task and a critical step prior to annotating protein coding regions in newly sequenced genomes or de novo transcriptome assemblies. With the tremendous increase in genomic and transcriptomic data, faster tools are needed to handle large input datasets. These tools should be versatile enough to fine-tune search criteria and allow efficient downstream analysis. Here we present a new python based tool, orfipy, which allows the user to flexibly search for open reading frames in genomic and transcriptomic sequences. The search is rapid and is fully customizable, with a choice of FASTA and BED output formats. AVAILABILITY AND IMPLEMENTATION: orfipy is implemented in python and is compatible with python v3.6 and higher. Source code: https://github.com/urmi-21/orfipy. Installation: from the source, or via PyPi (https://pypi.org/project/orfipy) or bioconda (https://anaconda.org/bioconda/orfipy). SUPPLEMENTARY INFORMATION: Supplementary data are available at https://github.com/urmi-21/orfipy and Bioinformatics online.
SUMMARY: Searching for open reading frames is a routine task and a critical step prior to annotating protein coding regions in newly sequenced genomes or de novo transcriptome assemblies. With the tremendous increase in genomic and transcriptomic data, faster tools are needed to handle large input datasets. These tools should be versatile enough to fine-tune search criteria and allow efficient downstream analysis. Here we present a new python based tool, orfipy, which allows the user to flexibly search for open reading frames in genomic and transcriptomic sequences. The search is rapid and is fully customizable, with a choice of FASTA and BED output formats. AVAILABILITY AND IMPLEMENTATION: orfipy is implemented in python and is compatible with python v3.6 and higher. Source code: https://github.com/urmi-21/orfipy. Installation: from the source, or via PyPi (https://pypi.org/project/orfipy) or bioconda (https://anaconda.org/bioconda/orfipy). SUPPLEMENTARY INFORMATION: Supplementary data are available at https://github.com/urmi-21/orfipy and Bioinformatics online.
Authors: Kyle M Benowitz; Carson W Allan; Benjamin A Degain; Xianchun Li; Jeffrey A Fabrick; Bruce E Tabashnik; Yves Carrière; Luciano M Matzkin Journal: Genetics Date: 2022-05-05 Impact factor: 4.402