aMAT is a computationally efficient and powerful method multi-trait association analysis. Compared with many existing methods, aMAT has two compelling features that make it potentially useful in many settings.
- First, aMAT yields well-controlled Type 1 error rates when analyzing any number (e.g., hundreds) of traits. In contrast, many competing methods yield incorrect Type 1 error rates.
- Second, aMAT maintains high statistical power (often more powerful than competing methods) over a wide range of scenarios.
In this repo, we provide the following sources:
- aMAT: the software for running aMAT
- Codes: sources codes for replicating the results present in the following manuscript: Chong Wu, Multi-trait genome-wide analyses of the brain imaging phenotypes in UK Biobank, Genetics, Under Revision.
The issue tickets at the GitHub repo are the primary interface for bug reporting, suggestions, and comments. Through this issue tackets repo, previous issues can be searched.
Chong Wu
GPL (>= 3)