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Tangram: a comprehensive toolbox for mobile element insertion detection.

Jiantao Wu, Wan-Ping Lee, Alistair Ward

  • 1Department of Human Genetics and USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, Utah, USA. gabor.marth@gmail.com.

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|September 18, 2014
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Summary
This summary is machine-generated.

Tangram accurately detects mobile element insertions (MEIs) and their genotypes using whole genome sequencing data. This new method offers superior sensitivity and specificity for identifying genetic variants linked to diseases.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Mobile elements (MEs) comprise over 50% of the human genome and are actively duplicating.
  • Mobile element insertions (MEIs) are linked to genetic disorders like cancer and Crohn's disease.
  • Accurate detection and genotyping of MEIs from next-generation sequencing (NGS) data are crucial but challenging for current tools.

Purpose of the Study:

  • To develop a computationally efficient method for detecting and genotyping mobile element insertions (MEIs).
  • To improve the sensitivity, specificity, and accuracy of MEI variant calling in whole genome sequencing data.

Main Methods:

  • Developed Tangram, a novel MEI detection program integrating read-pair (RP) and split-read (SR) mapping signals.
  • Utilized SR mapping as a primary detection module for single-nucleotide precision breakpoint identification.
  • Validated Tangram's performance using simulations and experimental datasets.

Main Results:

  • Tangram achieves superior sensitivity, specificity, and breakpoint resolution compared to existing MEI detection methods.
  • The software accurately determines sample genotypes for MEI variants.
  • Demonstrated high performance in pinpointing MEI breakpoints with single-nucleotide precision.

Conclusions:

  • Tangram is a highly accurate and efficient tool for mobile element insertion detection and genotyping.
  • The program is implemented as a portable, memory-efficient C++ application under an open-source model.
  • Tangram is utilized as the primary MEI detection tool in the 1000 Genomes Project.