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Open Access Highly Accessed Research article

How accurate can genetic predictions be?

Jonathan M Dreyfuss12*, Daniel Levner34, James E Galagan56, George M Church34 and Marco F Ramoni178

  • * Corresponding author: Jonathan M Dreyfuss

  • † Equal contributors

Author Affiliations

1 Partners Center for Personalized Genetic Medicine, Boston, MA, 02115, USA

2 Graduate Program in Bioinformatics, Boston University, Boston, MA, 02215, USA

3 Department of Genetics, Harvard Medical School, Boston, MA, 02115, USA

4 Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, 02115, USA

5 Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA

6 Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA

7 Harvard-MIT Division of Health Sciences and Technology, Boston, MA, 02139, USA

8 Children’s Hospital Informatics Program, Boston, MA, 02115, USA

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BMC Genomics 2012, 13:340  doi:10.1186/1471-2164-13-340

Published: 24 July 2012

Additional files

Additional file 1:

Table of maximum AUCs. These are the maximum AUCs corresponding to Figure 2 for all values of prevalence. Row names represent values of heritability (computed on the observed binary scale) or proportion of phenotypic variance explained, and column names represent values of prevalence.

Format: XLS Size: 105KB Download file

This file can be viewed with: Microsoft Excel Viewer

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Additional file 2:

Table of maximum sensitivities for each specificity. Rows represent the combination of heritability (H.sq, computed on the observed binary scale) and prevalence (Prev), while columns represent specificities. The elements are the maximal sensitivity in each case.

Format: XLS Size: 36KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional file 3:

Archive containing instructions (readme.txt) and computer code (maxAcc.r) to implement our algorithms. The code is written in the free statistical language and environment R ( webcite), relies on free R optimization packages, and is copyrighted by the permissive MIT license ( webcite). Updated versions are freely available for download at: webcite.

Format: ZIP Size: 7KB Download file

Open Data