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WISARD: workbench for integrated superfast association studies for related datasets
Sungyoung Lee1, Sungkyoung Choi2, Dandi Qiao3
1Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea.
BMC Medical Genomics
|April 27, 2018
Summary
The Workbench for Integrated Superfast Association studies for Related Data (WISARD) efficiently analyzes genetic data from extended families. This tool enhances genetic association studies and outperforms existing methods for complex disease research.
Area of Science:
- Genetics
- Bioinformatics
- Epidemiology
Background:
- Family-based studies are crucial for genetic epidemiology, aiding heritability and association analyses.
- Advancements in genotyping enable whole-genome sequencing for studies, including de novo mutation detection.
- Existing family-based genetic analyses often involve complex algorithms and rarely use extended family data.
Purpose of the Study:
- To develop a computational tool for efficient analysis of genetic data in extended families.
- To facilitate genetic association studies using SNP-chip and next-generation sequencing data.
- To improve accessibility of complex genetic analyses for researchers.
Main Methods:
- Developed the Workbench for Integrated Superfast Association studies for Related Data (WISARD) in C/C++.
- Enabled multithreaded processing for rapid analysis of extended family genetic data.
- Integrated R software for data visualization to enhance user accessibility.
Main Results:
- WISARD provides fast and comprehensive analysis of SNP-chip and sequencing data from extended families.
- The tool supports applications from study design to results summarization.
- WISARD demonstrated superior performance compared to existing toolsets in computational suitability and speed.
Conclusions:
- WISARD is computationally efficient for integrated analysis of related subjects.
- The tool was successfully applied to a large-scale chronic obstructive pulmonary disease (COPD) dataset.
- WISARD identified multiple genes associated with COPD, highlighting its practical utility in genetic research.
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