Evidence map›Paper›PMID 36916756›Full record

ArticleBioinformatics (Oxford, England)2023

vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines.

Elisabet Munté, Lidia Feliubadaló, Marta Pineda, Eva Tornero, Maribel Gonzalez, José Marcos Moreno-Cabrera, Carla Roca, Joan Bales Rubio, Laura Arnaldo, Gabriel Capellá and 2 more

Open access · goldFull text read
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. 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
3.3field-weighted citation impact, top 8% 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, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
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

12 authors at 1 institution in 1 country.

Elisabet MuntéHereditary Cancer Program, Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, Catalan Institute of Oncology, L'Hospitalet de Llobregat 08908, Spain.ORCID 0000-0001-8396-8284
Lidia FeliubadalóHereditary Cancer Program, Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, Catalan Institute of Oncology, L'Hospitalet de Llobregat 08908, Spain.ORCID 0000-0002-1736-0112
Marta PinedaHereditary Cancer Program, Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, Catalan Institute of Oncology, L'Hospitalet de Llobregat 08908, Spain.
Eva TorneroHereditary Cancer Program, Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, Catalan Institute of Oncology, L'Hospitalet de Llobregat 08908, Spain.
Maribel GonzalezHereditary Cancer Program, Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, Catalan Institute of Oncology, L'Hospitalet de Llobregat 08908, Spain.
José Marcos Moreno-CabreraHereditary Cancer Program, Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, Catalan Institute of Oncology, L'Hospitalet de Llobregat 08908, Spain.ORCID 0000-0001-8570-0345
Carla RocaHereditary Cancer Program, Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, Catalan Institute of Oncology, L'Hospitalet de Llobregat 08908, Spain.
Joan Bales RubioDepartment of Information Technologies, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat 08908, Spain.
Laura ArnaldoHereditary Cancer Program, Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, Catalan Institute of Oncology, L'Hospitalet de Llobregat 08908, Spain.
Gabriel CapelláHereditary Cancer Program, Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, Catalan Institute of Oncology, L'Hospitalet de Llobregat 08908, Spain.
Jose Luis MosqueraDepartment of Bioinformatics, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat 08908, Spain.ORCID 0000-0002-7852-4993
Conxi LázaroHereditary Cancer Program, Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, Catalan Institute of Oncology, L'Hospitalet de Llobregat 08908, Spain.
Institut d'Investigació Biomédica de Bellvitge · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationGermline variant classification allows accurate genetic diagnosis and risk assessment. However, it is a tedious iterative process integrating information from several sources and types of evidence. It should follow gene-specific (if available) or general updated international guidelines. Thus, it is the main burden of the incorporation of next-generation sequencing into the clinical setting.

resultsWe created the vaRiants in HC (vaRHC) R package to assist the process of variant classification in hereditary cancer by: (i) collecting information from diverse databases; (ii) assigning or denying different types of evidence according to updated American College of Molecular Genetics and Genomics/Association of Molecular Pathologist gene-specific criteria for ATM, CDH1, CHEK2, MLH1, MSH2, MSH6, PMS2, PTEN, and TP53 and general criteria for other genes; (iii) providing an automated classification of variants using a Bayesian metastructure and considering CanVIG-UK recommendations; and (iv) optionally printing the output to an .xlsx file. A validation using 659 classified variants demonstrated the robustness of vaRHC, presenting a better criteria assignment than Cancer SIGVAR, an available similar tool. AVAILABILITY AND IMPLEMENTATION: The source code can be consulted in the GitHub repository (https://github.com/emunte/vaRHC) Additionally, it will be submitted to CRAN soon.

Indexed as

Genetic VariationNeoplasmsAutomationBayes TheoremGenetic Predisposition to DiseaseGenetic TestingGenome, HumanHumansUnited States

Identifiers

PMID36916756
PMCPMC10032633
OpenAlexW4324128701

What OpenQuestion holds

Textfull text, public
LicenceCC BY
reference markers read5
measurements read57
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.