orfipy: a fast and flexible tool for extracting ORFs

Abstract

Searching for ORFs in transcripts is a critical step prior to annotating coding regions in newly-sequenced genomes and to search for alternative reading frames within known genes. With the tremendous increase in RNA-Seq 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 fasta 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). Contact: usingh@iastate.edu, mash@iastate.edu Supplementary information: Supplementary data are available at https://github.com/urmi-21/orfipy .

easyfm: An easy software suite for file manipulation of Next Generation Sequencing data on desktops

“…Long ORFs are often used, along with other evidence, to initially identify candidate protein-coding regions or functional RNA-coding regions in a given DNA sequence, but the presence of an ORF does not necessarily mean that the region is always translated [24]. As BLAST and BLAT, the web-based ORF Finder (https://www.ncbi.nlm.nih.gov/orffinder/), ORF Predictor (http://bioinformatics.ysu.edu/tools/OrfPredictor.html) and command-line tools (ORF Investigator [25] and orfipy [13]) offer a range of ORF searches, but its usage can be challenging for biologists due to lack of computer programming literacy and limited query sequence length. To maximise the flexibility, the easyfm ORF provides a fast and efficient approach for all possible translation and extraction of ORFs from nucleotide sequences (FASTA format of nucleotide and protein output from six-frame translation) (Fig 4).…”

“…Conveniently, FASTQ files can also be converted to FASTA files, the most commonly used file format for NGS data that enables direct sequencing of target genes. Many available tools (easySEARCH [10]; BlasterJS [11]; Sequenceserver [12]; orfipy [13]); Samtools and BCFtools [14] including easyfm ) have not surprisingly focused on manipulating (analyse, collect, organise, interpret, and present data in meaningful ways) the FASTA file format to generate biologically relevant insights.…”

Foster thy young: Enhanced prediction of orphan genes in assembled genomes

“…Protein sequence used as evidence in MAKER 30 were generated in one of two ways: 1) For Arabidopsis, yeast, and rice, RNA-Seq reads were assembled using Trinity (v2.6.6) 65 , followed by open reading frame (ORF) prediction and translation using orfipy 29 or TransDecoder (v3.0.1) 65 . 2) For Arabidopsis only, data was downloaded from Phytozome 66 as predicted protein sequences for nine species: Arabidopsis thaliana, (Glycine max, Populus trichocarpa, Arabidopsis lyrata, Conradina grandiflora, Setaria italica, Oryza sativa, Physcomitrella patens, Chlamydomonas reinhardtii, and Brassica rapa).…”

“…The BAM file generated by mapping reads to the Araport11-annotated indexed genome using HiSat2 (v2.1.0) 67 was provided as training for the assemblers. The resultant assembled transcripts were used to predict ORFs using Transdecoder 65 or orfipy 29 . We selected those complete ORFs over 150 nt.…”

“…This approach is key for predicting non-coding RNAs 28 and young genes 3 .However, it has been less widely adopted to annotate protein coding genes, in part because of the challenge of distinguishing "noise" from true genetic signal 26,27 . One approach to reduce "noise" and other false positive predictions is to combine direct inference of genes with sequence similarity 24,26 ; this approach excludes orphan genes 29 .…”