Editing Open reading frame (section)

==Software==

===Finder===
The ORF Finder (Open Reading Frame Finder)<ref>{{cite web|url=https://www.ncbi.nlm.nih.gov/orffinder/|title=ORFfinder|website=National Center for Biotechnology Information }}</ref> is a graphical analysis tool which finds all open reading frames of a selectable minimum size in a user's sequence or in a sequence already in the database. This tool identifies all open reading frames using the standard or alternative genetic codes. The deduced amino acid sequence can be saved in various formats and searched against the sequence database using the [[BLAST (biotechnology)|basic local alignment search tool]] (BLAST) server. The ORF Finder should be helpful in preparing complete and accurate sequence submissions. It is also packaged with the Sequin sequence submission software (sequence analyser).

===Investigator===
ORF Investigator<ref>{{cite journal | vauthors = Dhar DV, Kumar MS |title=ORF Investigator: A New ORF finding tool combining Pairwise Global Gene Alignment |journal=Research Journal of Recent Sciences |date=2012 |volume=1 |issue=11 |pages=32–35}}</ref> is a program which not only gives information about the coding and non coding sequences but also can perform pairwise global alignment of different gene/DNA regions sequences. The tool efficiently finds the ORFs for corresponding amino acid sequences and converts them into their single letter amino acid code, and provides their locations in the sequence. The pairwise global alignment between the sequences makes it convenient to detect the different mutations, including [[single nucleotide polymorphism]]. [[Needleman–Wunsch algorithm]]s are used for the gene alignment. The ORF Investigator is written in the portable [[Perl]] [[programming language]], and is therefore available to users of all common operating systems.

===Predictor===
OrfPredictor<ref>{{cite web|url=http://bioinformatics.ysu.edu/tools/OrfPredictor.html|title=OrfPredictor|website=bioinformatics.ysu.edu|access-date=2015-12-17|archive-date=2015-12-22|archive-url=https://web.archive.org/web/20151222082631/http://bioinformatics.ysu.edu/tools/OrfPredictor.html|url-status=dead}}</ref> is a web server designed for identifying protein-coding regions in expressed sequence tag (EST)-derived sequences. For query sequences with a hit in BLASTX, the program predicts the coding regions based on the translation reading frames identified in BLASTX alignments, otherwise, it predicts the most probable coding region based on the intrinsic signals of the query sequences. The output is the predicted peptide sequences in the [[FASTA format]], and a definition line that includes the query ID, the translation reading frame and the nucleotide positions where the coding region begins and ends. OrfPredictor facilitates the annotation of EST-derived sequences, particularly, for large-scale EST projects.

ORF Predictor uses a combination of the two different ORF definitions mentioned above. It searches stretches starting with a start codon and ending at a stop codon. As an additional criterion, it searches for a stop codon in the 5' [[untranslated region]] (UTR or NTR, ''nontranslated region''<ref name="Carrington_1990">{{cite journal | vauthors = Carrington JC, Freed DD | title = Cap-independent enhancement of translation by a plant potyvirus 5' nontranslated region | journal = Journal of Virology | volume = 64 | issue = 4 | pages = 1590–7 | date = April 1990 | pmid = 2319646 | pmc = 249294 | doi = 10.1128/JVI.64.4.1590-1597.1990 }}</ref>). The OrfPredictor web server was not further supported, the standalone OrfPredictor tool can be downloaded at the following site (http://bioinformatics.ysu.edu/publication/tools_download/).

===ORFik===
ORFik is a R-package in Bioconductor for finding open reading frames and using Next generation sequencing technologies for justification of ORFs.<ref>{{cite journal|url=https://bioconductor.org/packages/release/bioc/html/ORFik.html|title=ORFik - Open reading frames in genomics|website=bioconductor.org|year=2018|doi=10.18129/B9.bioc.ORFik|last1=Kornel Labun|first1=Haakon Tjeldnes}}</ref><ref>{{cite journal | doi=10.1186/s12859-021-04254-w | title=ORFik: A comprehensive R toolkit for the analysis of translation | year=2021 | last1=Tjeldnes | first1=Håkon | last2=Labun | first2=Kornel | last3=Torres Cleuren | first3=Yamila | last4=Chyżyńska | first4=Katarzyna | last5=Świrski | first5=Michał | last6=Valen | first6=Eivind | journal=BMC Bioinformatics | volume=22 | issue=1 | page=336 | pmid=34147079 | pmc=8214792 | doi-access=free }}</ref>

=== orfipy ===
orfipy is a tool written in [[Python (programming language) |Python]] / [[Cython]] to extract ORFs in an extremely and fast and flexible manner.<ref>{{cite journal | vauthors = Singh U, Wurtele ES | title = orfipy: a fast and flexible tool for extracting ORFs | journal = Bioinformatics | date = February 2021 | volume = 37 | issue = 18 | pages = 3019–3020 | pmid = 33576786 | doi = 10.1093/bioinformatics/btab090| issn=1367-4803  | pmc = 8479652 | doi-access = free }}</ref> orfipy can work with plain or gzipped FASTA and FASTQ sequences, and provides several options to fine-tune ORF searches; these include specifying the start and stop codons, reporting partial ORFs, and using custom translation tables. The results can be saved in multiple formats, including the space-efficient BED format. orfipy is particularly faster for data containing multiple smaller FASTA sequences, such as de-novo transcriptome assemblies.<ref>{{Citation| vauthors = Singh U |title=urmi-21/orfipy|date=2021-02-13|url=https://github.com/urmi-21/orfipy|access-date=2021-02-13}}</ref>