I run mixer bivarate model on 2 traits named CP and OP and then plot the figure using the following commands
python mixer_figures.py two --json-fit fit.json --json-test test.json --out output --trait1 CP --trait2 OP --statistic mean std --ext svg
The plot I made is attached.
I have two questions regarding it
1), in the first plot (the one on the left), the number of shared variants is 9.6k, which means the best genetic overlap model of 9.6k should have the lowest -logL. But, the model with the lowest -logL on the forth plot (the one on the right) is somewher around 10.5k? Why two number aren't the same?
2), the bivaraite -logL plot displayed in the mixer github AIC/BIC interpretation section (github main page) only has a clean line. But in my plot, I have a line with a lot of dots around it. What does these dots and line mean? And why it differs from the one on the main github page?
I run mixer bivarate model on 2 traits named CP and OP and then plot the figure using the following commands python mixer_figures.py two --json-fit fit.json --json-test test.json --out output --trait1 CP --trait2 OP --statistic mean std --ext svg The plot I made is attached. I have two questions regarding it 1), in the first plot (the one on the left), the number of shared variants is 9.6k, which means the best genetic overlap model of 9.6k should have the lowest -logL. But, the model with the lowest -logL on the forth plot (the one on the right) is somewher around 10.5k? Why two number aren't the same? 2), the bivaraite -logL plot displayed in the mixer github AIC/BIC interpretation section (github main page) only has a clean line. But in my plot, I have a line with a lot of dots around it. What does these dots and line mean? And why it differs from the one on the main github page?
Best, Charley