Evidence map›Paper›PMID 39501379›Full record

ReviewHuman genomics2024

Best practices for germline variant and DNA methylation analysis of second- and third-generation sequencing data.

Ferdinando Bonfiglio, Andrea Legati, Vito Alessandro Lasorsa, Flavia Palombo, Giulia De Riso, Federica Isidori, Silvia Russo, Simone Furini, Giuseppe Merla, Fabio Coppedè and 7 more

Abstract readReview
In one paragraph

Review in Human genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Functional genomic analysis ofCurrent research in microbial sciences · 2025
    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

17 authors.

Ferdinando BonfiglioDepartment of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy.
Andrea LegatiFondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.
Vito Alessandro LasorsaCEINGE Advanced Biotechnology Franco Salvatore, Naples, Italy.
Flavia PalomboProgramma Di Neurogenetica, IRCCS Istituto Delle Scienze Neurologiche Di Bologna, Bologna, Italy.
Giulia De RisoDepartment of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy.
Federica IsidoriIRCCS Azienda Ospedaliero-Universitaria Di Bologna, Bologna, Italy.
Silvia RussoResearch Laboratory of Medical Cytogenetics and Molecular Genetics, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Simone FuriniDepartment of Electrical, Electronic and Information Engineering "Guglielmo Marconi", University of Bologna, Bologna, Italy.
Giuseppe MerlaDepartment of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy.
Fabio CoppedèDepartment of Translational Research and of New Surgical and Medical Technologies, University of Pisa, Pisa, Italy.
Marco TartagliaMolecular Genetics and Functional Genomics, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.
Omics Sciences - Bioinformatics and Epigenetics Working Groups of the Italian Society of Human Genetics (SIGU)
Alessandro BrusellesDepartment of Oncology and Molecular Medicine, Istituto Superiore Di Sanità, Rome, Italy.
Tommaso PippucciIRCCS Azienda Ospedaliero-Universitaria Di Bologna, Bologna, Italy.
Andrea CiolfiMolecular Genetics and Functional Genomics, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.
Michele PinelliDepartment of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy.
Mario CapassoDepartment of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy. mario.capasso@unina.it.

Funding

Associazione Oncologia Pediatrica e Neuroblastoma ONLUS EDITORFondazione Italiana per la Lotta al Neuroblastoma GENEDREN
6 · The paper itself

Abstract

This comprehensive review provides insights and suggested strategies for the analysis of germline variants using second- and third-generation sequencing technologies (SGS and TGS). It addresses the critical stages of data processing, starting from alignment and preprocessing to quality control, variant calling, and the removal of artifacts. The document emphasized the importance of meticulous data handling, highlighting advanced methodologies for annotating variants and identifying structural variations and methylated DNA sites. Special attention is given to the inspection of problematic variants, a step that is crucial for ensuring the accuracy of the analysis, particularly in clinical settings where genetic diagnostics can inform patient care. Additionally, the document covers the use of various bioinformatics tools and software that enhance the precision and reliability of these analyses. It outlines best practices for the annotation of variants, including considerations for problematic genetic alterations such as those in the human leukocyte antigen region, runs of homozygosity, and mitochondrial DNA alterations. The document also explores the complexities associated with identifying structural variants and copy number variations, underscoring the challenges posed by these large-scale genomic alterations. The objective is to offer a comprehensive framework for researchers and clinicians, ensuring that genetic analyses conducted with SGS and TGS are both accurate and reproducible. By following these best practices, the document aims to increase the diagnostic accuracy for hereditary diseases, facilitating early diagnosis, prevention, and personalized treatment strategies. This review serves as a valuable resource for both novices and experts in the field, providing insights into the latest advancements and methodologies in genetic analysis. It also aims to encourage the adoption of these practices in diverse research and clinical contexts, promoting consistency and reliability across studies.

Indexed as

DNA MethylationGerm-Line MutationHigh-Throughput Nucleotide SequencingComputational BiologyDNA Copy Number VariationsGerm CellsHumansSequence Analysis, DNASoftwareBioinformaticsDNA methylationGenetic diagnosticsGermline variantsHereditary diseasesNGS

Identifiers

PMID39501379
PMCPMC11536923

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.