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Toolbox for mobile-element insertion detection on cancer genomes.

Wan-Ping Lee1, Jiantao Wu2, Gabor T Marth3

  • 1Department of Biology, Boston College, Chestnut Hill, MA, USA. ; Currently at Seven Bridges Genomics, Cambridge, MA, USA.

Cancer Informatics
|December 3, 2014
PubMed
Summary

TANGRAM software now detects mobile-element insertions (MEIs) using any short-read mapper, improving cancer genome analysis. This advancement makes MEI detection more accessible for researchers studying genomic evolution and disease.

Keywords:
ALUmobile-element insertionstructural variation

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Mobile elements comprise over 45% of the human genome.
  • Active mobile elements like ALU, LINE1, and SVA can cause diseases, including cancer.
  • Accurate detection of mobile-element insertions (MEIs) is crucial for understanding genomic diseases.

Purpose of the Study:

  • To enhance the TANGRAM software for mobile-element insertion (MEI) detection.
  • To enable TANGRAM to process alignments from any mainstream short-read mapper.
  • To demonstrate TANGRAM's utility in cancer genome analysis.

Main Methods:

  • TANGRAM software was updated to accept alignments from diverse short-read mappers.
  • The enhanced TANGRAM was applied to the TCGA mutation calling benchmark 4 dataset.
  • Performance was evaluated for speed, accuracy, and ease of use.

Main Results:

  • TANGRAM now supports alignments from any mainstream short-read mapper.
  • The software demonstrated utility in analyzing cancer genomes.
  • TANGRAM is presented as a fast, accurate, and user-friendly tool.

Conclusions:

  • The updated TANGRAM software broadens accessibility for MEI detection in genomic research.
  • TANGRAM is a valuable tool for mobile-element insertion analysis, particularly in cancer genomics.
  • The open-source availability facilitates widespread adoption and further development.