ReviewFrontiers in bioinformatics2025
Artificial intelligence in variant calling: a review.
Review in Frontiers in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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.
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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
16 citing papers in PubMed.
- Decoding cancer with artificial intelligence: Transforming research, diagnosis, and therapy with future insights.Translational oncology · 2026Review
- Reanalysis of genomic data doubles the diagnostic yield for Welsh patients recruited to the UK 100,000 Genomes Project.European journal of human genetics : EJHG · 2026Article
- AI in variant analysis: fast track to genetic diagnoses.Human genetics · 2026Review
- A Novel Approach to Interrogating Whole Genome Sequencing Data to Optimise Clinical Utility.Molecular genetics & genomic medicine · 2026Article
- How precise are mutation rate estimates? Comparison of different approaches to estimate de novo mutation rates.Heredity · 2026Article
- DNA Profiling in forensic genetics and anthropogenetics: Techniques, databases, and ethical considerations.Forensic science, medicine, and pathology · 2026Review
- Building genomic medicine in Saudi Arabia.Nature genetics · 2026Article
- Exploring the strengths and limitations of AI-driven variant prioritization versus manual curation in inborn errors of immunity.Frontiers in genetics · 2026Article
- Genomic innovations in cancer prevention, diagnosis, prognosis and precision therapeutics.Frontiers in genetics · 2026Review
- Artificial intelligence in haematology laboratory diagnosis: Current applications, challenges, and future directions.African journal of laboratory medicine · 2026Review
- Imagining Genomics and Population Health in 2050: Anticipating Future Research, Policy, and Governance Needs.Public health genomics · 2026Article
- The expanding role of artificial intelligence in personalised medicine: from innovation to individualized care.Frontiers in medicine · 2026Review
- Article
- Bioinformatics and artificial intelligence in genomic data analysis: current advances and future directions.Molecular genetics and genomics : MGG · 2025Review
- Evaluating gene variations in autosomal dominant polycystic kidney disease patients using whole exome sequencing and phenotype to genotype analysis.Renal failure · 2025Article
- Transgene Mapping in Animals: What to Choose?International journal of molecular sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has revolutionized numerous fields, including genomics, where it has significantly impacted variant calling, a crucial process in genomic analysis. Variant calling involves the detection of genetic variants such as single nucleotide polymorphisms (SNPs), insertions/deletions (InDels), and structural variants from high-throughput sequencing data. Traditionally, statistical approaches have dominated this task, but the advent of AI led to the development of sophisticated tools that promise higher accuracy, efficiency, and scalability. This review explores the state-of-the-art AI-based variant calling tools, including DeepVariant, DNAscope, DeepTrio, Clair, Clairvoyante, Medaka, and HELLO. We discuss their underlying methodologies, strengths, limitations, and performance metrics across different sequencing technologies, alongside their computational requirements, focusing primarily on SNP and InDel detection. By comparing these AI-driven techniques with conventional methods, we highlight the transformative advancements AI has introduced and its potential to further enhance genomic research.
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Registered trials
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.