Software packages that accompany methodology papers are often available (Hu et al., 2014; Wu et al., 2011; Yandell et al., 2011). While they implement useful methods, they typically do not provide sufficient features that are necessary for practical data analyses. It is necessary to develop software tools and pipelines that enable statistical analysis of sequence data which is otherwise cumbersome to perform. A few software packages are available for performing comprehensive sequence-based association analyses, including Variant Association Tools (VAT; Wang et al., 2014) and PSEQ (https://atgu.mgh.harvard.edu/plinkseq/index.shtml). Despite their convenient and useful features, the tools are slower in managing and performing association analyses for large sequence datasets. Moreover, to our knowledge, neither tool supports the linear mixed model analyses of (cryptically) related samples. Instead, RVTESTS is designed to be able to efficiently handle large datasets in a moderately configured computer server. In our benchmarks, for a computer server with 64 GB RAM, RVTESTS can analyze 64 000 individuals with a linear mixed model or >100 000 individuals using a (generalized) linear model.
