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Updated: Jul 21, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Estimating error rates for single molecule protein sequencing experiments.

Matthew Beauregard Smith^1,2, 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

This summary is machine-generated.

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.

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Last Updated: Jul 21, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

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Published on: August 3, 2018

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Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

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Published on: August 17, 2015

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.