Towards Democratizing CNS Tumor Classification: 10-fold reduction in methylation sequencing cost with the Flongle Flow Cell
Year: 2026
Type: preprint
Abstract: Oxford Nanopore Technologies-based methylation profiling enables rapid, accurate CNS tumor classification but is currently mostly performed with MinION flow cells (~$1,000 USD). We benchmarked the low-cost Flongle flow cell (~$100, 10-fold reduction) for methylation-based tumor classification. Across 12 pediatric CNS tumor samples with highly variable sequencing yields (17–330 Mbp), both Sturgeon and nanoDx classifiers achieved perfect diagnostic accuracy when operating above significance thresholds, despite extreme data sparsity. Bootstrap analysis determined empirically defined minimum data thresholds. These results demonstrate that Flongle flow cells enable cost-effective deployment of rapid, accurate nanopore-based CNS diagnostics while maintaining clinical reliability.
Source: medRxiv
Institutions: Tel Aviv University, Schneider Children's Medical Center
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7212077473