SAM-dPCR: Real-Time and High-throughput Absolute Quantification of Biological Samples Using Zero-Shot Segment Anything Model
arxiv(2024)
摘要
Digital PCR (dPCR) has revolutionized nucleic acid diagnostics by enabling
absolute quantification of rare mutations and target sequences. However,
current detection methodologies face challenges, as flow cytometers are costly
and complex, while fluorescence imaging methods, relying on software or manual
counting, are time-consuming and prone to errors. To address these limitations,
we present SAM-dPCR, a novel self-supervised learning-based pipeline that
enables real-time and high-throughput absolute quantification of biological
samples. Leveraging the zero-shot SAM model, SAM-dPCR efficiently analyzes
diverse microreactors with over 97.7
of 3.16 seconds. By utilizing commonly available lab fluorescence microscopes,
SAM-dPCR facilitates the quantification of sample concentrations. The accuracy
of SAM-dPCR is validated by the strong linear relationship observed between
known and inferred sample concentrations. Additionally, SAM-dPCR demonstrates
versatility through comprehensive verification using various samples and
reactor morphologies. This accessible, cost-effective tool transcends the
limitations of traditional detection methods or fully supervised AI models,
marking the first application of SAM in nucleic acid detection or molecular
diagnostics. By eliminating the need for annotated training data, SAM-dPCR
holds great application potential for nucleic acid quantification in
resource-limited settings.
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