Additional file 3: Figure S2. of A biologically informed method for detecting rare variant associations

Wilcoxon type I error per biological feature. QQ plots for the type I error Wilcoxon Rank Sum analysis showing the p-value distribution from the average gene (a), XL gene (b), and pathway (c) simulations. The different colors represent various BioBin weighting schemes analyzed. (PNG 147 kb

Additional file 1: of A biologically informed method for detecting rare variant associations

Script for generating reference sequence. Python script used to generate a reference sequence file for input into SeqSIMLA2 simulation software. The allele frequency file used in the script was obtained by parsing the protein coding regions of the autosomes in the 1000 Genomes Project VCF file. Additional specifications include the number of reference samples to generate and the number of markers to include in the reference file. (DOCX 14 kb

Additional file 2: Figure S1. of A biologically informed method for detecting rare variant associations

Logistic regression type I error per biological feature. QQ plots for the type I error logistic regression analysis showing the p-value distribution from the average gene (a), XL gene (b), and pathway (c) simulations. The different colors represent various BioBin weighting schemes analyzed. (PNG 170 kb

Additional file 2: of A simulation study investigating power estimates in phenome-wide association studies

Summary Results: The summary results used to generate the figures. (XLSX 56 kb

Additional file 1: of A simulation study investigating power estimates in phenome-wide association studies

Figure S1. Binary Trait Type I Errors. The plot shows the Type I errors for different parameter settings. Each panel represents the different case number on the top and case-control ratio on the right which was used for the simulation dataset. The Type I error on the y-axis is calculated based on the number of false positive association below significance level of α = 0.00025. The disease penetrance is represented on the x-axis and each colored point represent different MAF used in the simulations. (PNG 379 kb

Quisqualis indica L.

原著和名: インドシクンシ科名: シクンシ科 = Combretaceae採集地: 千葉県 千葉市 千葉大学 (下総 千葉市 千葉大学)採集日: 1974/7/6採集者: 萩庭丈壽整理番号: JH007681国立科学博物館整理番号: TNS-VS-95768

Additional file 4: Table S4. of eMERGE Phenome-Wide Association Study (PheWAS) identifies clinical associations and pleiotropy for stop-gain variants

Dataset 2 results at p-value significance of 0.01. (XLSX 58 kb

Additional file 3: Table S3. of eMERGE Phenome-Wide Association Study (PheWAS) identifies clinical associations and pleiotropy for stop-gain variants

Dataset 1 results at p-value significance of 0.01. (XLSX 67 kb

Additional file 1: Table S1. of Identifying gene-gene interactions that are highly associated with Body Mass Index using Quantitative Multifactor Dimensionality Reduction (QMDR)

Information for cohorts providing individual level data. Information regarding the geographic location, and numbers of individuals included from each cohort. (PDF 40 kb

Additional file 6:Â Additional Acknowledgements. of Identifying gene-gene interactions that are highly associated with Body Mass Index using Quantitative Multifactor Dimensionality Reduction (QMDR)

Acknowledgements and detailed descriptions of the five studies that provided the data for the analyses in this paper. (PDF 68 kb