MOTIVATION: The increasing adoption of clinical whole-genome resequencing (WGS) 
demands for highly accurate and reproducible variant calling (VC) methods. The 
observed discordance between state-of-the-art VC pipelines, however, indicates 
that the current practice still suffers from non-negligible numbers of false 
positive and negative SNV and INDEL calls that were shown to be enriched among 
discordant calls but also in genomic regions with low sequence complexity.
RESULTS: Here, we describe our method ReliableGenome (RG) for partitioning 
genomes into high and low concordance regions with respect to a set of surveyed 
VC pipelines. Our method combines call sets derived by multiple pipelines from 
arbitrary numbers of datasets and interpolates expected concordance for genomic 
regions without data. By applying RG to 219 deep human WGS datasets, we 
demonstrate that VC concordance depends predominantly on genomic context rather 
than the actual sequencing data which manifests in high recurrence of regions 
that can/cannot be reliably genotyped by a single method. This enables the 
application of pre-computed regions to other data created with comparable 
sequencing technology and software. RG outperforms comparable efforts in 
predicting VC concordance and false positive calls in low-concordance regions 
which underlines its usefulness for variant filtering, annotation and 
prioritization. RG allows focusing resource-intensive algorithms (e.g. consensus 
calling methods) on the smaller, discordant share of the genome (20-30%) which 
might result in increased overall accuracy at reasonable costs. Our method and 
analysis of discordant calls may further be useful for development, benchmarking 
and optimization of VC algorithms and for the relative comparison of call sets 
between different studies/pipelines.
AVAILABILITY AND IMPLEMENTATION: RG was implemented in Java, source code and 
binaries are freely available for non-commercial use at 
https://github.com/popitsch/wtchg-rg/ CONTACT: niko@wtchg.ox.ac.ukSupplementary 
information: Supplementary data are available at Bioinformatics online.