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Related Concept Videos

Genome Copying Errors02:46

Genome Copying Errors

DNA replication is a well-evolved process that copies millions of base pairs with high fidelity during each cell division. Occasionally a wrong base or a long stretch of wrong bases may get added to the daughter strands. If the errors are left unchecked, cells might accumulate several mutations that might endanger their  survival. Therefore, the copying errors are checked and repaired at three levels.
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Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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Mismatch Repair01:20

Mismatch Repair

Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
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Next-generation Sequencing03:00

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Although all next-generation methods use different technologies, they all share a set of standard features.

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Related Experiment Video

Updated: May 20, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Analysis of context-dependent errors for illumina sequencing.

Irina Abnizova1, Steven Leonard, Tom Skelly

  • 1Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK. ia1@sanger.ac.uk

Journal of Bioinformatics and Computational Biology
|July 20, 2012
PubMed
Summary
This summary is machine-generated.

Accurate SNP calling requires evaluating sequencing error probabilities and the "second best call" probability. This method corrects approximately 80% of mismatches, improving variant calling reliability.

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Last Updated: May 20, 2026

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06:59

Using Next Generation Sequencing to Identify Mutations Associated with Repair of a CAS9-induced Double Strand Break Near the CD4 Promoter

Published on: March 31, 2022

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Short-read sequencing technologies are advancing, necessitating robust data quality metrics.
  • Accurate variant calling, particularly for Single Nucleotide Polymorphisms (SNPs), is crucial but challenged by false positives.
  • Distinguishing true SNPs from sequencing errors is a significant hurdle in genetic analysis.

Purpose of the Study:

  • To develop improved methods for distinguishing true SNPs from false positives in sequencing data.
  • To enhance the reliability of SNP calling by incorporating novel quality measures.
  • To reduce the rate of false-positive SNPs in next-generation sequencing data.

Main Methods:

  • Utilizing the probability of sequencing errors (quality value) and the conditional probability of the "second best call" to assess SNP accuracy.
  • Analyzing nucleotide context and mismatch types to identify error-prone DNA motifs.
  • Developing a method based on the conditional probability of the "second best intensity call" to correct mismatches.
  • Assigning a "second call" confidence value to each mismatch for correction assessment.

Main Results:

  • The "second best call" probability significantly aids in distinguishing false-positive SNPs from true variants.
  • Approximately 80% of mismatches can be effectively "corrected" using this secondary call probability.
  • Identifying and assigning quality values to error-prone DNA motifs further reduces false SNP rates.
  • Context-based measures effectively differentiate sequencing errors from candidate SNPs.

Conclusions:

  • Integrating "second best call" probabilities and context-aware quality values substantially improves SNP calling accuracy.
  • The proposed methods offer a reliable approach to mitigate false positives in short-read sequencing data.
  • This work provides a valuable tool for enhancing the precision of variant detection in genomic studies.