Abstract: The disclosure relates to analysing genetic data. In one arrangement, a method operates on input data comprising strengths of association between one or more phenotypes including a target phenotype and a plurality of genetic variants. A fine-mapping algorithm is applied to all or a subset of the input data to identify one or more independent phenotype-variant associations. A set of one or more fine-mapped variants is identified for each association. A fine-mapping predictive model is calculated on the basis of the input data and the set of fine-mapped variants. The effect on the target phenotype of the set of fine-mapped variants is subtracted from the input data to obtain residual association data. A machine learning algorithm is applied to the residual association data to identify further predictive correlations between the target phenotype and the plurality of genetic variants.

Abstract: Methods are disclosed for analysing genetic data about an organism. In one arrangement, input units are derived from studies that provide information about the association between genetic variants and phenotypes. Input units are assigned to one of a plurality of clusters, based on an assessment of the extent to which input units share genetic variants that affect any aspect of the phenotype corresponding to each input unit or any of the underlying biological mechanisms of the phenotype, thereby identifying phenotypes that share underlying biological mechanisms.