Closed Y-Isaac closed 5 months ago
@Y-Isaac this error comes from SuSiE, so I can't address it in full. It seems like something is unusual in the LD in this region. This sometimes happens e.g. in long-range LD regions (like the HLA region).
I would try looking at Issue #176 in the SuSiE GitHub repo, and the diagnostics they refer to. If this still doesn't work, you can try opening an issue in the SuSiE repo.
Sorry I can't help more, hopefully this will push you in the right direction.
Thanks for your help!
HI,
I'm coming across an issue that it would be helpful to have your insight on. I applied Polyfun+Susie on multiple phenotypes, and the majority of the results were normal, but one phenotype showed a little high frequency of warnings: "IBSS algorithm did not converge in 100 iterations!" (57 warnings/ 1419 loci). To save computational resources, I randomly sampled 10% of the samples and used their genetic data as a reference. Thus, I suspect there is an inconsistency between summary statistics and the LD matrix, as mentioned in the log file. However, when I tried using a completely consistent LD reference, the warning still persisted.
Therefore, I tried other methods: First, I included the parameter --susie-max-iter 200. Even with 200 iterations, the IBSS still did not converge. After checking the results, I found only a little differences(no substantial difference). I am considering increasing the iteration limit further (e.g., to 500), but intuitively, this does not seem like a reliable approach.
Second, I used HESS with the parameter --hess-min-h2 1e-4 and the default 100 iterations. The warning persisted, and the results only slightly differed from those obtained using Susie's built-in estimator (also with 100 iterations), but also no substantial difference. I also tried adding the parameter susie-resvar-init 0.9, but the results did not change.
Third, I used the susie-resvar-hess parameter, as you suggested in #56. This led to a new error:
This seems to be due to the residual variance being less than zero. Now, I am eager to receive your guidance on how to solve this problem. Thank you in advance for your help!