Efficient Bayesian mixed-model analysis increases association power in large cohorts
Linear mixed models are a powerful statistical tool for identifying genetic associations and avoiding confounding. However, existing methods are computationally intractable in large cohorts and may not optimize power. All existing methods require time cost O(MN2) (where N is the number of samples an...
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Nature Publishing Group
2017
|
| Online Access: | http://hdl.handle.net/1721.1/110185 https://orcid.org/0000-0003-3864-9828 https://orcid.org/0000-0002-2724-7228 |