Evidence map›Paper›PMID 31974522›Full record

ArticleScientific reports2020

ISOGO: Functional annotation of protein-coding splice variants.

Juan A Ferrer-Bonsoms, Ignacio Cassol, Pablo Fernández-Acín, Carlos Castilla, Fernando Carazo, Angel Rubio

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 34% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Predicting the Structural Impact of Human Alternative Splicing.bioRxiv : the preprint server for biology · 2023
    Article
  5. Article
  6. Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 2 countries.

Juan A Ferrer-Bonsoms *Department of Biomedical Engineering and Sciences, Tecnun-Universidad de Navarra, Manuel de Lardizábal 15, 20018, San Sebastián, Spain.
Ignacio Cassol *Department of Bioengineering, Facultad de Ingeniería, Universidad Austral, Mariano Acosta, 1611, Buenos Aires, Argentina.
Pablo Fernández-AcínDepartment of Biomedical Engineering and Sciences, Tecnun-Universidad de Navarra, Manuel de Lardizábal 15, 20018, San Sebastián, Spain.
Carlos CastillaDepartment of Biomedical Engineering and Sciences, Tecnun-Universidad de Navarra, Manuel de Lardizábal 15, 20018, San Sebastián, Spain.
Fernando CarazoDepartment of Biomedical Engineering and Sciences, Tecnun-Universidad de Navarra, Manuel de Lardizábal 15, 20018, San Sebastián, Spain.
Angel RubioDepartment of Biomedical Engineering and Sciences, Tecnun-Universidad de Navarra, Manuel de Lardizábal 15, 20018, San Sebastián, Spain. arubio@tecnun.es.
Centro de Estudios e Investigaciones Técnicas de Gipuzkoa · ESAustral University · ARUniversidad de Navarra · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advent of RNA-seq technologies has switched the paradigm of genetic analysis from a genome to a transcriptome-based perspective. Alternative splicing generates functional diversity in genes, but the precise functions of many individual isoforms are yet to be elucidated. Gene Ontology was developed to annotate gene products according to their biological processes, molecular functions and cellular components. Despite a single gene may have several gene products, most annotations are not isoform-specific and do not distinguish the functions of the different proteins originated from a single gene. Several approaches have tried to automatically annotate ontologies at the isoform level, but this has shown to be a daunting task. We have developed ISOGO (ISOform + GO function imputation), a novel algorithm to predict the function of coding isoforms based on their protein domains and their correlation of expression along 11,373 cancer patients. Combining these two sources of information outperforms previous approaches: it provides an area under precision-recall curve (AUPRC) five times larger than previous attempts and the median AUROC of assigned functions to genes is 0.82. We tested ISOGO predictions on some genes with isoform-specific functions (BRCA1, MADD,VAMP7 and ITSN1) and they were coherent with the literature. Besides, we examined whether the main isoform of each gene -as predicted by APPRIS- was the most likely to have the annotated gene functions and it occurs in 99.4% of the genes. We also evaluated the predictions for isoform-specific functions provided by the CAFA3 challenge and results were also convincing. To make these results available to the scientific community, we have deployed a web application to consult ISOGO predictions (https://biotecnun.unav.es/app/isogo). Initial data, website link, isoform-specific GO function predictions and R code is available at https://gitlab.com/icassol/isogo.

Indexed as

AlgorithmsAlternative SplicingGene OntologyHumansMolecular Sequence AnnotationOpen Reading FramesProtein IsoformsProtein Isoforms

Identifiers

PMID31974522
PMCPMC6978412
OpenAlexW3001041731

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.