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Estimating error rates for single molecule protein sequencing experiments
Matthew Beauregard Smith1,2, Kent VanderVelden3, Thomas Blom3
1Oden Institute, The University of Texas at Austin, Austin, TX 78712.
Biorxiv : the Preprint Server for Biology
|July 28, 2023
Summary
Accurate error rate estimation is crucial for single molecule protein sequencing (SMPS) technologies. We developed two methods, including a Hidden Markov Model (HMM) approach, to accurately estimate SMPS error rates for fluorosequencing applications.
Area of Science:
- Biotechnology
- Computational Biology
- Proteomics
Background:
- Single molecule protein sequencing (SMPS) technologies are emerging but require precise error rate estimation for practical use.
- Fluorosequencing is a key SMPS technique, necessitating robust methods for analyzing its associated error profiles.
Conclusions:
- The developed parameter estimation methods, particularly the HMM-based approach, offer principled ways to assess SMPS fluorosequencing error rates.
- Accurate error rate estimation is vital for advancing the practical application and reliability of single molecule protein sequencing technologies.
