False-positive rates in two-point parametric linkage analysis

Challenges of linkage analysis in the era of whole-genome sequencing

Whole-genome sequencing (WGS) is becoming an affordable technology for the study of the genetics of complex traits. With any new technology, experimental designs and statistical methods, both old and new, must be evaluated. One design seeing a resurgence of interest is the use of families. Genetic Analysis Workshop 18 provided the opportunity to evaluate statistical methods applied to WGS data for family-based studies. We summarize the results of five contributions that used linkage in the context of WGS. The investigators took differing approaches, including assessment of false-positive rates in classic two-point linkage, the effects of heterogeneity on linkage and association tests, and the use of linkage to focus association tests. We describe the primary findings of each contribution and note challenges that are not new to those working in family designs or specific to WGS data; for example, choice of phenotype definition, covariate adjustment, and use of longitudinal data may produce different results, making comparisons challenging. We detail new issues brought about by WGS, such as the elevated genome-wide false-positive rate for classic two-point parametric linkage analysis, computational demands in multipoint calculations, and lack of clarity in how to best use linkage to focus association testing. Finally, we comment on when linkage may be helpful for WGS, highlighting where additional research is needed; for example, although linkage analysis has been successful in the study of rare variants of large effect, how to best use family information in the context of rare variants of moderate effect remains an open research question.