Table 2.
Select sORF and SEP databases and resourcesa
| Primary use | Resource | ORF/SEP supporting evidence | Notable features | URL | Refs |
|---|---|---|---|---|---|
| Visualization | GWIPS-Viz | Ribo-Seq, Ti-Seq and RNA-Seq visualization from individual experiments and global aggregates | Online genome browser for visualizing processed Ribo-Seq data | https://gwips.ucc.ie/ | [59] |
| Trips-Viz | Ribo-Seq and MS data from individual experiments | Online browser for visualizing processed Ribo-Seq data. Can plot single nucleotide read intensity and predict translated ORFs | https://trips.ucc.ie/ | [60] | |
| Transcriptome-wide ORF predictions | RPFdb v2.0 | Ribo-Seq | Comprehensive collection of Ribo-Seq studies with ORF predictions in a searchable browser | http://sysbio.gzzoc.com/rpfdb/index.html | [61] |
| sORFs.org | Conservation Ribo-Seq MS |
Incorporates multiple sORF scoring metrics and annotates sORFs with dozens of attributes | http://www.sorfs.org/ | [62] | |
| Metamorf | Conservation Coding potential Kozak context Ribo-Seq MS |
Includes UCSC genome browser session for visualization and introduces an ORF nomenclature | https://metamorf.hb.univ-amu.fr/ | [63] | |
| smProt | Literature mining Database mining Ribo-Seq MS |
Includes variant and disease specific annotations and maintains a high-confidence set | http://bigdata.ibp.ac.cn/SmProt/ | [64] | |
| OpenProt | Ribo-Seq MS |
Generates ORFeome by 3-frame transcriptome translation, then checks for evidence of translation | https://www.openprot.org/ | [65] | |
| nORFs.org |
sORFs.org
openProt.org |
Aggregates information from other databases and presents a fast, user-friendly interface, including a built-in genome browser | https://norfs.org/home | [66] | |
| ORFs in noncoding RNA | LncPEP | Coding potential Conserved protein domains Ti-Seq Ribo-Seq m6A RNA modification |
Focuses on lncRNAs. Determines a coding score based on a normalized sum of six input variables | http://www.shenglilabs.com/LncPep/ | [67] |
| SPENCER | MS | SEPs from ncRNA in cancer including predictions of MHC I affinity, stability, and TCR recognition probability | http://spencer.renlab.org/#/home | [68] | |
| Coding and noncoding RNA database | Literature review | Curated RNAs that have coding and noncoding functions with links to literature and supporting data | http://www.rna-society.org/cncrnadb/ | [69] | |
| Ribo-Seq web application | RiboToolkit | Predictions from uploaded FASTQs | Webserver that accepts Ribo-Seq FASTQs for analysis and implements a full prediction pipeline | http://rnabioinfor.tch.harvard.edu/RiboToolkit/ | [41] |
These resources enable investigators to circumvent the technical and computational challenges of sORF prediction and move directly to the hypothesis-driven characterization phase. Indeed, given the thousands of predicted but unstudied sORFs, the greater benefit to the scientific community collectively might come from investigations of current predictions rather than new exploratory experiments.