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Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
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Using XHMM Software to Detect Copy Number Variation in Whole-Exome Sequencing Data
Menachem Fromer1,2,3, Shaun M Purcell1,2,3
1Division of Psychiatric Genomics and Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York.
Current Protocols in Human Genetics
|April 26, 2014
Summary
Copy number variation (CNV) detection from exome sequencing data is challenging. We developed XHMM, a statistical tool to accurately identify CNVs and aid biological analyses.
Area of Science:
- Genetics
- Bioinformatics
- Computational Biology
Background:
- Copy number variation (CNV) is a significant genetic factor in human diseases.
- Exome sequencing is increasingly used to study large sample cohorts for genetic variations.
- Detecting CNVs from exome sequencing data presents challenges due to signal-to-noise ratio issues.
Purpose of the Study:
- To introduce XHMM, a novel set of statistical and computational tools for CNV detection.
- To provide detailed instructions for running XHMM.
- To guide the use of XHMM-generated CNV calls in biological research.
Main Methods:
- Development of a statistical and computational framework named XHMM.
- Implementation of algorithms to differentiate true CNV signals from noise in exome sequencing data.
- Detailed protocol for XHMM execution and output interpretation.
Main Results:
- XHMM effectively identifies copy number variations from exome sequencing data.
- The tool assists in distinguishing relevant genetic signals from background noise.
- The methodology enables the application of CNV data in downstream biological studies.
Conclusions:
- XHMM provides a robust solution for CNV detection in exome sequencing.
- The tool facilitates the integration of CNV data into disease research.
- XHMM enhances the utility of exome sequencing for genetic variation analysis.
Keywords:
Hidden Markov Model (HMM)copy number variation (CNV)data normalizationnext-generation sequencing (NGS)principal component analysis (PCA)More Related Videos
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