ReviewFrontiers in aging2021
Identification of Somatic Mutations From Bulk and Single-Cell Sequencing Data.
Review in Frontiers in aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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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
14 citing papers in PubMed, 19 citations in OpenAlex.
- Somatic mosaicism in the brain: linking development, ageing and neurodegeneration.Nature reviews. Neurology · 2026Review
- Article
- Article
- Somatic mosaicism in ALS and FTD identifies focal mutations associated with widespread degeneration.Nature genetics · 2026Article
- Article
- Detecting somatic variants in purified brain DNA obtained from surgically implanted depth electrodes in epilepsy.Epilepsia · 2025Article
- Single-Cell Sequencing: Genomic and Transcriptomic Approaches in Cancer Cell Biology.International journal of molecular sciences · 2025Review
- Reconstructing developmental lineages: a retrospective approach using somatic mutations and variant allele frequency.Frontiers in genetics · 2025Review
- Human embryonic genetic mosaicism and its effects on development and disease.Nature reviews. Genetics · 2024Review
- Chasing Sequencing Perfection: Marching Toward Higher Accuracy and Lower Costs.Genomics, proteomics & bioinformatics · 2024Review
- Somatic cancer driver mutations are enriched and associated with inflammatory states in Alzheimer's disease microglia.bioRxiv : the preprint server for biology · 2024Article
- Technological and computational approaches to detect somatic mosaicism in epilepsy.Neurobiology of disease · 2023Review
- Cell-by-Cell: Unlocking Lung Cancer Pathogenesis.Cancers · 2022Review
- MAST: a hybrid Multi-Agent Spatio-Temporal model of tumor microenvironment informed using a data-driven approach.Bioinformatics advances · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Somatic mutations are DNA variants that occur after the fertilization of zygotes and accumulate during the developmental and aging processes in the human lifespan. Somatic mutations have long been known to cause cancer, and more recently have been implicated in a variety of non-cancer diseases. The patterns of somatic mutations, or mutational signatures, also shed light on the underlying mechanisms of the mutational process. Advances in next-generation sequencing over the decades have enabled genome-wide profiling of DNA variants in a high-throughput manner; however, unlike germline mutations, somatic mutations are carried only by a subset of the cell population. Thus, sensitive bioinformatic methods are required to distinguish mutant alleles from sequencing and base calling errors in bulk tissue samples. An alternative way to study somatic mutations, especially those present in an extremely small number of cells or even in a single cell, is to sequence single-cell genomes after whole-genome amplification (WGA); however, it is critical and technically challenging to exclude numerous technical artifacts arising during error-prone and uneven genome amplification in current WGA methods. To address these challenges, multiple bioinformatic tools have been developed. In this review, we summarize the latest progress in methods for identification of somatic mutations and the challenges that remain to be addressed in the future.
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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.