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Integrated variant allele frequency analysis pipeline and R package: easyVAF
Junxiao Hu1,2, Vida Alami1, Yonghua Zhuang1,2
1Biostatistics Shared Resource (RRID: SCR_021981), University of Colorado Cancer Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
Molecular Carcinogenesis
|August 22, 2023
Summary
easyVAF is a new R package for comparing variant allele frequencies (VAFs) across groups to identify cancer-associated genetic changes. It offers statistical tests to analyze VAFs, aiding in cancer research and treatment response evaluation.
Area of Science:
- Genomics
- Bioinformatics
- Cancer Research
Background:
- Somatic sequence variants are crucial for cancer diagnosis, prognosis, and treatment response.
- Variant allele frequency (VAF) quantifies mutation rates and reflects tumor clonal evolution.
- Existing tools lack comprehensive VAF comparison capabilities across groups.
Purpose of the Study:
- To develop an R package, easyVAF, for comparing VAFs among and between groups.
- To provide statistical tests for identifying significant genetic loci.
- To offer an interactive R Shiny app for VAF analysis.
Main Methods:
- Development of the R package easyVAF.
- Inclusion of parametric and nonparametric statistical tests for VAF comparison.
- Evaluation using simulated scenarios and comparison with existing tests.
Main Results:
- easyVAF provides a pipeline for VAF analysis, from quality checking to group comparison.
- The package offers three statistical tests to balance power and type I error rate.
- The beta-binomial likelihood ratio test is recommended for sparse data.
Conclusions:
- easyVAF facilitates the identification of key genetic loci through VAF comparison.
- Choosing appropriate statistical tests is critical for accurate VAF analysis.
- The package and its app enhance VAF analysis in cancer research.
Keywords:
VAFVAF comparisonbeta-binomial distributionclonal composition of tumorslikelihood ratio teststatistical powertumor feature detectionMore Related Videos
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