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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Updated: Nov 4, 2025

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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Selection of Optimal Bioinformatic Tools and Proper Reference for Reducing the Alignment Error in Targeted Sequencing

Hannane Mohammadi Nodehi1, Mohammad Amin Tabatabaiefar2,3, Mohammadreza Sehhati1

  • 1Department of Bioelectric and Biomedical Engineering, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

Journal of Medical Signals and Sensors
|May 24, 2021
PubMed
Summary
This summary is machine-generated.

A new framework improves next-generation sequencing mapping accuracy in targeted regions. Using a Customized Target-Based Reference (CTBR) with Stampy alignment significantly reduced mapping errors, enhancing variant calling in clinical studies.

Keywords:
Chromosomeshigh-throughput nucleotide sequencingsequence analysis

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Next-generation sequencing (NGS) study design is crucial for accurate downstream analysis.
  • Sequence mapping is a critical step in targeted sequencing studies.

Purpose of the Study:

  • To propose a framework for evaluating and enhancing sequence mapping in targeted genomic regions.
  • To compare mapping performance using a Customized Target-Based Reference (CTBR) against standard references.

Main Methods:

  • Simulated short reads from human coding regions were generated.
  • Reads were mapped to a CTBR and standard references using recent alignment tools.
  • Mapping accuracy, unmapped/misaligned reads, and runtime were measured, including analysis with introduced mutations.

Main Results:

  • The CTBR with Stampy alignment demonstrated significantly higher mapping accuracy compared to other pipelines.
  • CTBR usage substantially decreased mapping errors versus expanded or limited references.
  • With introduced mutations, Stampy using CTBR achieved a minimum error of 1.67%, outperforming standard references (3.78% to 20% error).

Conclusions:

  • The proposed framework can predict and mitigate errors in clinical targeted sequencing.
  • Implementing this framework can improve variant calling performance for targeted genomic regions in clinical settings.