Table 1.
Comparison of running time of RHE-mc, GCTA-mc, and BOLT-REML.
| Parameters | Running time (h) | ||||
|---|---|---|---|---|---|
| N | M | K | RHE-mc | GCTA-mc | BOLT-REML |
| 10,000 | 459,792 | 22 | <1 | 1.3 | 1 |
| 100,000 | 459,792 | 22 | <1 | – | 40 |
| 291,273 | 459,792 | 22 | <1 | – | 162 |
| 291,273 | 459,792 | 300 | <1 | – | – |
| 291,273 | 4,824,392 | 8 | 3.2 | – | – |
| 1,000,000 | 1,000,000 | 8 | 3 | – | – |
| 1,000,000 | 1,000,000 | 100 | 12.4 | – | – |
Here M, N, and K are the number of SNPs, individuals, and variance components, respectively. RHE-mc can run efficiently even on datasets with one million individuals and SNPs as well as efficiently computing hundreds of variance components. All comparisons were performed on an Intel(R) Xeon(R) CPU 2.10 GHz server with 128 GB RAM.