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Towards accurate characterization of clonal heterogeneity based on structural variation
Xian Fan, Wanding Zhou, Zechen Chong
1Department of Bioinformatics and Computational Biology, The University of Texas M,D, Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA. kchen3@mdanderson.org.
BMC Bioinformatics
|September 10, 2014
Summary
This study introduces a new method to estimate allele fractions for structural variants, aiding in the analysis of tumor clonal heterogeneity. The BreakDown tool enables better characterization of genomically unstable tumors using these variants.
Area of Science:
- Genomics
- Cancer Biology
- Bioinformatics
Background:
- Deep digital sequencing reveals significant clonal heterogeneity in tumor DNA.
- Accurate estimation of allele fractions is crucial for understanding somatic mutations.
- Structural variants offer potential for more precise allele fraction estimation than substitutions or indels.
Purpose of the Study:
- To develop a systematic method for estimating allele fractions of structural variants.
- To enable the analysis of clonal heterogeneity using structural variants.
- To enhance the characterization of genomically unstable tumors.
Main Methods:
- Developed a novel maximum-likelihood method for integrative allele fraction estimation.
- Created a tool named BreakDown to implement the method.
- The method analyzes various alignment signals for structural variants.
Main Results:
- BreakDown estimates allele fractions for medium-sized deletions, duplications, inversions, and translocations.
- The method integrates diverse alignment signals for comprehensive analysis.
- Demonstrated the capability to estimate allele fractions for a wide range of structural variants.
Conclusions:
- The developed method systematically enables the use of structural variants for clonal heterogeneity analysis.
- BreakDown significantly enhances the characterization of genomically unstable tumors.
- Evaluation using simulated and real data confirms the method's effectiveness.
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