Evidence map›Paper›PMID 36361767›Full record

ReviewInternational journal of molecular sciences2022

Exploration of Tools for the Interpretation of Human Non-Coding Variants.

Nicole Tabarini, Elena Biagi, Paolo Uva, Emanuela Iovino, Tommaso Pippucci, Marco Seri, Andrea Cavalli, Isabella Ceccherini, Marta Rusmini, Federica Viti

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. The Role of Genetic Testing in Adult CKD.Journal of the American Society of Nephrology : JASN · 2024
    Article
  10. Article
  11. WGS Revealed NovelInternational journal of molecular sciences · 2023
    Article
  12. Resources and tools for rare disease variant interpretation.Frontiers in molecular biosciences · 2023
    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

10 authors.

Nicole TabariniComputational and Chemical Biology, Italian Institute of Technology, 16163 Genoa, Italy.ORCID 0000-0003-2409-8746
Elena BiagiDepartment of Medical and Surgical Sciences, University of Bologna, 40138 Bologna, Italy.ORCID 0000-0002-8573-3603
Paolo UvaClinical Bioinformatics, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy.ORCID 0000-0002-9524-8492
Emanuela IovinoDepartment of Medical and Surgical Sciences, University of Bologna, 40138 Bologna, Italy.
Tommaso PippucciMedical Genetics Unit, IRCCS Sant'Orsola-Malpighi University Hospital, 40138 Bologna, Italy.
Marco SeriDepartment of Medical and Surgical Sciences, University of Bologna, 40138 Bologna, Italy.ORCID 0000-0003-2425-2176
Andrea CavalliComputational and Chemical Biology, Italian Institute of Technology, 16163 Genoa, Italy.
Isabella CeccheriniUOSD Laboratory of Genetics and Genomics, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy.ORCID 0000-0001-8732-1955
Marta RusminiUOSD Laboratory of Genetics and Genomics, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy.ORCID 0000-0002-3109-413X
Federica VitiComputational and Chemical Biology, Italian Institute of Technology, 16163 Genoa, Italy.

Funding

Italian Ministry of Health RF-2018-12366314
6 · The paper itself

Abstract

The advent of Whole Genome Sequencing (WGS) broadened the genetic variation detection range, revealing the presence of variants even in non-coding regions of the genome, which would have been missed using targeted approaches. One of the most challenging issues in WGS analysis regards the interpretation of annotated variants. This review focuses on tools suitable for the functional annotation of variants falling into non-coding regions. It couples the description of non-coding genomic areas with the results and performance of existing tools for a functional interpretation of the effect of variants in these regions. Tools were tested in a controlled genomic scenario, representing the ground-truth and allowing us to determine software performance.

Indexed as

GenomicsSoftwareGenomeGenome, HumanHumansWhole Genome Sequencing5′UTRmutation intolerancenon-coding variantssplicing predictionvariant prioritizationwhole genome sequencing

Identifiers

PMID36361767
PMCPMC9654743

What OpenQuestion holds

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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.