Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects

Hundreds of thousands of human whole genome sequencing (WGS) datasets will be generated over the next few years. These data are more valuable in aggregate: joint analysis of genomes from many sources increases sample size and statistical power. A central challenge for joint analysis is that different WGS data processing pipelines cause substantial differences in variant calling in combined datasets, necessitating computationally expensive reprocessing. This approach is no longer tenable given the scale of current studies and data volumes. Here, we define WGS data processing standards that allow different groups to produce functionally equivalent (FE) results, yet still innovate on data processing pipelines. We present initial FE pipelines developed at five genome centers and show that they yield similar variant calling results and produce significantly less variability than sequencing replicates. This work alleviates a key technical bottleneck for genome aggregation and helps lay the foundation for community-wide human genetics studies.


Other Contributors

Regier AA1, Farjoun Y2, Larson DE1, Krasheninina O3, Kang HM4, Howrigan DP2, Chen BJ5,6, Kher M5, Banks E2, Ames DC7, English AC8, Li H2, Xing J9, Zhang Y9, Matise T9, Abecasis GR4, Salerno W3, Zody MC5, Neale BM10,11, Hall IM12.