simple proposals and experiments in Bayesian inference of free energy and path selection for cryo-EM.
Alex Barnett, Pilar Cossio, et al... June 2021.
See notes
and utils
for Alex's stuff.
Pilar's group added a new folder 2DHsp90 with 3 subfolders:
Files in folder:
- Num_Images_grid: number of images at each x,y point (in matrix form 20 by 20). This is the 'scatter plot'.
- 2D-FES_plot.py: python code to graph FES using Num_Images_grid and the two reference paths (black and orange). Run: python3.6 2D-FES_plot.py Output: 3-wells-paths.png
LikeLihood: Data for calculating the log-likelihood given a predetermined path and G that maximizes it.
Files in folder:
- likelihood_calc.py: calculates the log-L (total and for each image) given a path and Gmax. Run: python3.6 likelihood_calc.py [FILE_PATH] [FILE_GMAX] > Log-L-image e.g., FILE_PATH=Path-black and FILE_GMAX=Gmax-black Output: log-L of individual images and final line total log-L.
- Path-black and Path-orange: Node indexes (following Julian's notation) of the black and orange paths
- Gmax-black and Gmax-orange: Gs that maximize cryoBIFE likelihood.
- all_images: LogP BioEM for all images (rows) and the 225 models (columns) within the green square (slide 8 alexdiscussion.pdf; typo there not 200 but 225)
Files in folder:
- cryoBIFE.py: MCMC from paper using Alex's logsumexp function. Run: python3.6 cryoBIFE.py [FILE_PATH] > LogL-[FILE_PATH] Output: LogL-[FILE_PATH] logL at each MCMC step, an additional output file "Gs" has the Gs at each MCMC step.
- get-max.sh: bash script to get Gs that maximize Log-L. Run: ./get-max.sh LogL-[FILE_PATH]
- Check-logsumexp: Checking the results from using Alex's routine and the old (correct) one that we had (see commented-out line 148 - 160)
- all_images: same as above.
- Path-black and Path-orange: same as above.