Evidence map›Paper›PMID 38271481›Full record

ReviewBriefings in bioinformatics2024

Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges.

Yury A Barbitoff, Mikhail O Ushakov, Tatyana E Lazareva, Yulia A Nasykhova, Andrey S Glotov, Alexander V Predeus

Open access · goldAbstract readReview
In one paragraph

Review in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
8.3field-weighted citation impact, top 2% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
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  5. Review
  6. Review
  7. Article
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  11. PLoV: a comprehensive database of genetic variants leading to pregnancy loss.Database : the journal of biological databases and curation · 2025
    Article
  12. Article
  13. Article
  14. 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

6 authors at 2 institutions in 1 country.

Yury A BarbitoffDpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, Mendeleevskaya line 3, 199034, St. Petersburg, Russia.ORCID 0000-0002-3222-440X
Mikhail O UshakovDpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, Mendeleevskaya line 3, 199034, St. Petersburg, Russia.
Tatyana E LazarevaDpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, Mendeleevskaya line 3, 199034, St. Petersburg, Russia.
Yulia A NasykhovaDpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, Mendeleevskaya line 3, 199034, St. Petersburg, Russia.
Andrey S GlotovDpt. of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, Mendeleevskaya line 3, 199034, St. Petersburg, Russia.
Alexander V PredeusBioinformatics Institute, Kentemirovskaya st. 2A, 197342, St. Petersburg, Russia.
Research Institute of Obstetrics and Gynecology named after D.O. Ott · RUBioinformatics Institute · RU

Funding

Ministry of Science and Higher Education of Russian Federation 075-15-2021-1058
6 · The paper itself

Abstract

Next-generation sequencing (NGS) has revolutionized the field of rare disease diagnostics. Whole exome and whole genome sequencing are now routinely used for diagnostic purposes; however, the overall diagnosis rate remains lower than expected. In this work, we review current approaches used for calling and interpretation of germline genetic variants in the human genome, and discuss the most important challenges that persist in the bioinformatic analysis of NGS data in medical genetics. We describe and attempt to quantitatively assess the remaining problems, such as the quality of the reference genome sequence, reproducible coverage biases, or variant calling accuracy in complex regions of the genome. We also discuss the prospects of switching to the complete human genome assembly or the human pan-genome and important caveats associated with such a switch. We touch on arguably the hardest problem of NGS data analysis for medical genomics, namely, the annotation of genetic variants and their subsequent interpretation. We highlight the most challenging aspects of annotation and prioritization of both coding and non-coding variants. Finally, we demonstrate the persistent prevalence of pathogenic variants in the coding genome, and outline research directions that may enhance the efficiency of NGS-based disease diagnostics.

Indexed as

Computational BiologyRare DiseasesGenome, HumanGenomicsGerm CellsHigh-Throughput Nucleotide SequencingHumansNGSreference genomevariant annotationvariant callingWES

Identifiers

PMID38271481
PMCPMC10810331
OpenAlexW4391232231

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.