ArticlePloS one2019
False-negative errors in next-generation sequencing contribute substantially to inconsistency of mutation databases.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Evaluation of false positive and false negative errors in targeted next generation sequencing.Genome biology · 2025Article
- All the sites we cannot see: Sources and mitigation of false negatives in RNA modification studies.Nature reviews. Molecular cell biology · 2025Review
- Enhancing Clinical Applications by Evaluation of Sensitivity and Specificity in Whole Exome Sequencing.International journal of molecular sciences · 2024Article
- Mitochondrial point heteroplasmy: insights from deep-sequencing of human replicate samples.BMC genomics · 2024Article
- Scalable inference of cell differentiation networks in gene therapy clonal tracking studies of haematopoiesis.Bioinformatics (Oxford, England) · 2023Article
- What makes TMB an ambivalent biomarker for immunotherapy? A subtle mismatch between the sample-based design of variant callers and real clinical cohort.Frontiers in immunology · 2023Article
- Technological Advances:Genes · 2022Article
- Distinct error rates for reference and nonreference genotypes estimated by pedigree analysis.Genetics · 2021Article
- Genetic Predisposition to Breast and Ovarian Cancers: How Many and Which Genes to Test?International journal of molecular sciences · 2020Review
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMore than 11,000 laboratories and companies developed their own next-generation sequencing (NGS) for screening and diagnosis of various diseases including cancer. Although inconsistencies of mutation calls as high as 43% in databases such as GDSC (Genomics of Drug Sensitivity in Cancer) and CCLE (Cancer Cell Line Encyclopedia) have been reported, not many studies on the reasons for the inconsistencies have been published. Methods: Targeted-NGS analysis of 151 genes in 35 cell lines common to GDSC and CCLE was performed, and the results were compared with those from GDSC and CCLE wherein whole-exome- or highly-multiplex NGS were employed.
resultsIn the comparison, GDSC and CCLE had a high rate (40-45%) of false-negative (FN) errors which would lead to high rate of inconsistent mutation calls, suggesting that highly-multiplex NGS may have high rate of FN errors. We also posited the possibility that targeted NGS, especially for the detection of low-level cancer cells in cancer tissues might suffer significant FN errors.
conclusionFN errors may be the most important errors in NGS testing for cancer; their evaluation in laboratory-developed NGS tests is needed.
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