VarB is a standalone C++ software tool, which visualizes (un)phased polymorphisms in a VCF file by sample, genetic region and quality. The basic inputs are a reference genome (fasta), variant (VCF) and annotation (gff) files. Complete genomes or user-specified regions (e.g. chromosome) may be inputted and viewed, with variant genotypes being colour coded. The variants displayed and their number will change depending on the quality and read depth filtering selected, allowing users to assess the robustness of the data and analysis. Sequence data with genes, exons, coding regions and strand-dependent codons are marked at appropriate zoom levels, and tracks summarizing GC content, relative variant density and results from data analysis are presented. The Tajimas D metric () (Tajima, 1989) is implemented and is a method for distinguishing between a DNA sequence evolving randomly (‘neutrally’, values close to 0) and one evolving under a non-random process, including directional selection (low negative values) or balancing selection (high positive values). The population differentiation Fst measure is also implemented (Weir, 1996) and quantifies allele frequency differences between user-specified populations, with values ranging between 0 (no difference) and 1 (complete differentiation). It is possible to export the graphics and analysis outputs. VarB was developed using the Qt cross-platform and user interface framework (qt-project.org).

We demonstrate the functionality of VarB using P. falciparum (Pf) whole-genome (14 chromosomes, 23 Mb, ~81% AT content) sequence data from Burkina Faso (BF, n = 25) and Thailand (n = 25). The raw data are from a Pf genomic diversity study (Manske et al., 2012; SRA Study ERP000190). The Illumina 54/76-base paired reads were mapped to the 3D7 reference genome (v3.0) using smalt (www.sanger.ac.uk/smalt) and processed as described previously (Robinson et al., 2011) to construct VCF (v4.1) files consisting of SNPs and indels. Across the 50 samples, 46 283 SNPs (density 1 every 500 bp) were identified and summarized in a combined VCF file. We focus on those 23 942 (51.7%) SNPs with minor alleles observed at least twice. Figure 1 (top) shows the SNP data (n = 1790 loci, 7.5%) for chromosome 10. Estimation of identified a large region (positioned ~1.4 Mb), potentially under balancing selection (). This region includes highly polymorphic antigenic-determining genes from the merozoite surface protein 3 family [msp3 (PF10_0345); msp3.8 (PF10_0355)], known to be under diversifying selection, and considered potential vaccine candidates (Ochola et al., 2010). By specifying the two population groups (BF and Thailand), the population differentiation measure Fst was calculated. There were 1153 (4.8%) SNPs with near or complete population differentiation (Fst values > 0.95) across the genome. Loci involved in anti-malarial drug resistance often show high differentiation (Wootton et al., 2002). Figure 1 (bottom) shows one region of interest in chromosome 7 containing the chloroquine resistance transporter (PfCRT, MAL7.1.27, maximum Fst 0.92). This locus is known to confer resistance to anti-malarial chloroquine-based drugs, with established differences in the haplotype structure between Southeast Asian and African isolates (Wootton et al., 2002). Other polymorphisms known to confer sulfadoxine-pyrimethamine drug resistance, namely regions around PfDHFR and PfDHPS genes (Pearce et al., 2009) had high Fst values (>0.80) (data not shown).

The translation of sequence variation into further laboratory experiments, treatments and point of care interventions, requires the ability to interrogate genomic data. VarB processes files of VCF format, displays the variants by position and quality as well as comparing them between groups to establish informative genetic markers and regions under selection. An advantage of the software is that it performs population and statistical analysis in real-time and does not require calculations to be performed elsewhere. We have presented data from 50 Pf isolates to demonstrate the utility of the software and highlighted regions with differing allele frequencies that coincide with known drug-resistance loci (e.g. PfCRT) as well as known vaccine candidates arising from considering regions under balancing selection (e.g. msp3.8). It is possible to process many hundreds of Pf or smaller genomes (e.g. bacterial) simultaneously. However, to aid processing of numerous much larger genomes, such as human, the software is capable of reading in single chromosomes. The modular computing architecture provides the flexibility to incorporate a number of extensions. These include the capacity to process BCF/BCF2 files, reading in informative meta tracks (e.g. genomic uniqueness), calculating other population genetic statistics and performing tests of association with a phenotype. Increased utility will also be possible through updates to the VCF format, to identify and annotate variants of greater size, such as large deletions.