RTG Population can use information from large sample sizes in the following ways:

Joint Population - all individuals from a large project analyzed simultaneously, reducing the coverage required per sample while delivering results significantly faster than alternative methods.

N+1 Analysis - a single individual (or small group) can be analyzed against a backdrop of prior information generated from a population dataset. This approach can save time and money, but RTG Population is able to maximize the utility of available prior information to improve accuracy.

Pedigree Aware - RTG Population uses pedigree information for single and multi-generation families to further improve calling accuracy and automatically highlight de novo variants.

Fast and scalable population handling

RTG jointly analyzes large case v. control and population scale research projects at speeds an order of magnitude faster than open source software. The population variant caller's speed and modest computer requirements allows to analyze samples iteratively, either fine tuning parameters, or adding more sample data as it becomes available to improve accuracy across all samples and provide consistent calls for SNVs, indels, and MNPs across the entire cohort.

N+1: Leveraging panels of reference samples

While joint calling of exome or whole genome data from cohorts improves quality, when the population samples become large the computational demands for calling grow. In order to leverage previously sequenced panels of reference samples in the calling of new samples (N+1), RTG Variant offers an innovative and very efficient solution, requiring only the previous calls of the reference panel as a slimed multisample VCF to be used as site specific priors and in the HWE maximization step of the population calling algorithm.  This delivers the accuracy benefits of joint calling with the execution time of single samples, a solution that only RTG Variant provides.

Comprehensive Analysis that Scales

For customers interested in identifying potentially causative variants underlying a disease or trait, known or suspected to follow a Mendelian pattern of inheritance, RTG delivers more accurate variant detection with less false positivies by integrating familial relationships during the alignment and calling process. Our Bayesian approach enables the joint analysis of multi-generational and extended pedigree analysis to identify variants present either sporadially or segregating under a variety of inheritance models: de novo dominant, inherited dominant, recessive (homozygous, compound heterozygous) and X-linked. Flexibility with respect to population structure and scale allows us to deliver a level of sensitivity that these studies are designed to uncover.