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Updated: Feb 26, 2026
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Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Published on: October 18, 2013
20.0K
Bioinformatics Data Analysis of Next-Generation Sequencing Data from Heterogeneous Tumor Samples.
Sean R Landman1, Tae Hyun Hwang2,3,4
1Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA.
Methods in Molecular Biology (Clifton, N.J.)
|July 24, 2017
Summary
Tumor heterogeneity poses challenges in cancer treatment and research. This study details genomics data analysis and pipelines for investigating tumor heterogeneity using next-generation sequencing data.
Area of Science:
- Genomics
- Cancer Research
- Bioinformatics
Background:
- Tumor heterogeneity presents a significant obstacle in cancer treatment and impedes research into the genetic origins of tumorigenesis.
- High-throughput sequencing technologies have become crucial for understanding genetic diseases and can be applied to study tumor heterogeneity.
Purpose of the Study:
- To provide an overview of genomics data analysis fundamentals.
- To describe analysis pipelines specifically designed for investigating tumor heterogeneity.
- To highlight the utility of next-generation sequencing data in cancer research.
Main Methods:
- Genomics data analysis principles.
- Development and description of bioinformatics pipelines.
- Application of next-generation sequencing (NGS) data.
Main Results:
- A foundational understanding of genomics data analysis is presented.
- Specific analysis pipelines for tumor heterogeneity are outlined.
- The application of NGS data for inferring tumor heterogeneity is demonstrated.
Conclusions:
- Genomics data analysis, particularly with NGS, is essential for addressing tumor heterogeneity.
- The described pipelines offer a framework for researchers studying the genetic basis of cancer.
- Advancing the understanding of tumor heterogeneity through data analysis can improve cancer treatment strategies.
