Abstract

Here, I describe the R package snpfiltr and demonstrate its functionality as the backbone of a customizable, reproducible single nucleotide polymorphism (SNP) filtering pipeline implemented exclusively via the widely adopted R programming language. SNPfiltR extends existing SNP filtering functionalities by automating the visualization of key parameters such as sequencing depth, quality, and missing data proportion, allowing users to visually optimize and implement filtering thresholds within a single, cohesive work session. All SNPfiltR functions require vcfr objects as input, which can be easily generated by reading a SNP data set stored in standard variant call format (vcf) into an R working environment using the function read.vcfR() from the R package vcfr. Performance and accuracy benchmarking reveal that for moderately sized SNP data sets (up to 50M genotypes, plus associated quality information), SNPfiltR performs filtering with comparable accuracy and efficiency to current state of the art command-line-based programs. These results indicate that for most reduced-representation genomic data sets, SNPfiltR is an ideal choice for investigating, visualizing, and filtering SNPs as part of a user friendly bioinformatic pipeline. The snpfiltr package can be downloaded from CRAN with the command install.packages("snpfiltr"), and the current development version is available from GitHub at: (github.com/DevonDeRaad/SNPfiltR). Thorough documentation for SNPfiltR, including multiple comprehensive vignettes detailing realistic use-cases, is available at the website: devonderaad.github.io/SNPfiltR/.

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