ArticleInternational journal of molecular sciences2025
Quantitative Analysis of Pseudogene-Associated Errors During Germline Variant Calling.
Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
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Who cites it
6 citing papers in PubMed.
- Functional roles and clinical implications of pseudogenes signatures as emerging biomarkers in cancer.Discover oncology · 2026Review
- Artificial Intelligence and Genomic Data Analysis: New Frontiers in Precision Medicine.International journal of molecular sciences · 2026Review
- The Role of Next-Generation Sequencing in Cardiovascular Disease: A New Era of Precision Cardiology.Life (Basel, Switzerland) · 2026Review
- Verification and comparison of pig, mouse, and human genome similarities: use of manual assembly and analyses.BMC genomics · 2025Article
- Bioinformatics and artificial intelligence in genomic data analysis: current advances and future directions.Molecular genetics and genomics : MGG · 2025Review
- A Hitchhiker Guide to Structural Variant Calling: A Comprehensive Benchmark Through Different Sequencing Technologies.Biomedicines · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
A pseudogene is a non-functional copy of a protein-coding gene. Processed pseudogenes, which are created by the reverse transcription of mRNA and subsequent integration of the resulting cDNA into the genome, being a major pseudogene class, represent a significant challenge in genome analysis due to their high sequence similarity to the parent genes and their frequent absence in the reference genome. This homology can lead to errors in variant identification, as sequences derived from processed pseudogenes can be incorrectly assigned to parental genes, complicating correct variant calling. In this study, we quantified the occurrence of variant calling errors associated with pseudogenes, generated by the most popular germline variant callers, namely GATK-HC, DRAGEN, and DeepVariant, when analysing 30x human whole-genome sequencing data (n = 13,307). The results show that the presence of pseudogenes can interfere with variant calling, leading to false positive identifications of potentially clinically relevant variants. Compared to other approaches, DeepVariant was the most effective in correcting these errors.
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Registered trials
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