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ARS Home » Pacific West Area » Corvallis, Oregon » Horticultural Crops Research Unit » Research » Publications at this Location » Publication #333957
Title: VCFR: A package to manipulate and visualize variant call format data in R

Author
item Knaus, Brian
item Grunwald, Niklaus - Nik

Submitted to: Molecular Ecology Resources
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/31/2016
Publication Date: 7/12/2016
Citation: Knaus, B.J., Grunwald, N.J. 2016. VCFR: A package to manipulate and visualize variant call format data in R. Molecular Ecology Resources. 17(1):44-53. doi: 10.1111/1755-0998.12549.

Interpretive Summary: Software to call single nucleotide polymorphisms or related genetic variants has converged on the variant call format (vcf) as their output format of choice. This has created a need for computational tools to work with vcf files. We created a set of functions and tools in the R computing language in a package called vcfR to address this issue. VcfR provides essential, novel tools currently not available in R for analyzing large data sets based on the vcf format.

Technical Abstract: Software to call single nucleotide polymorphisms or related genetic variants has converged on the variant call format (vcf) as their output format of choice. This has created a need for tools to work with vcf files. While an increasing number of software exists to read vcf data, many of them only extract the genotypes without including the data associated with each genotype that describes its quality. We created the R package vcfR to address this issue. We developed a vcf file exploration tool implemented in the R language because R provides an interactive experience and it is an environment that is commonly used for genetic data analysis. Functions to read and write vcf files into R as well as functions to extract portions of the data and to plot summary statistics of the data are implemented. VcfR further provides the ability to visualize how various parameterizations of the data affect the results. Additional tools are included to integrate sequence (fasta) and annotation data (gff) for visualization of genomic regions such as chromosomes. Conversion functions translate data from the vcfR data structure to formats used by other R genetics packages. Computationally intensive functions are implemented in C++ to improve performance. Use of these tools is intended to facilitate vcf data exploration, including intuitive methods for data quality control and easy export to other R packages for further analysis. VcfR thus provides essential, novel tools currently not available in R.