SNPs could potentially be used to identify individuals, and so we are not able to make data open that links SNP values to phenotypes. However, we have 1. Used synthpop to generate a dataset with the same characteristics. 2. Deposited covariance matrices and means for SNP and phenotype data for both SCT cases and one twin sample. 3. Deposited original data for phenotype variables. **Synthpop_sct.csv** contains data simulated using the R package synthpop. **synthpop_twina.csv** has analogous data simulated for twinA sample. Synthpop takes as its input a raw data file and creates synthetic data that have similar distributions and covariances. This allows for other users to explore the files without compromising confidentiality. The Markdown file **Double hit results.rmd** includes a chunk of code that details how synthpop files are created. The files **realcovs_sct.csv** and **realcovs_twina.csv** contain the covariance matrices for SNP and phenotype data, for SCT cases and twinA respectively, with column means in the last row. **osf_pheno_sct_twin.csv** has original data for phenotype variables, with any identifying information removed. The variables are described in **data_dictionary_phenotype_data.xls**