Gctf provides accurate estimation of the contrast transfer function (CTF) for near-atomic resolution cryo electron microscopy (cryoEM) reconstruction using GPUs. The main target of Gctf is to maximize the cross-correlation of a simulated CTF with the logarithmic amplitude spectra (LAS) of observed micrographs after background subtraction.
Gctf can utilize GPUs. This requires the user load the proper CUDA library for the executables. For example, the executable Gctf-v1.06_sm_30_cu7.5_x86_64 requires module load CUDA/7.5 prior to use.
Alternatively, a wrapper script which automatically loads the correct CUDA library can be used: Gctf
Allocate an interactive session, along with at least one GPU, and run the program. Sample session:
[user@biowulf]$ sinteractive --constraint=gpup100 --gres=gpu:p100:1 salloc.exe: Pending job allocation 46116226 salloc.exe: job 46116226 queued and waiting for resources salloc.exe: job 46116226 has been allocated resources salloc.exe: Granted job allocation 46116226 salloc.exe: Waiting for resource configuration salloc.exe: Nodes cn3144 are ready for job [user@cn3144 ~]$ module load Gctf CUDA/7.5 [user@cn3144 ~]$ Gctf-v1.06_sm_30_cu7.5_x86_64 --apix 1.07 --kV 300 --Cs 2.7 --ac 0.1 Micrographs/Falcon*.mrc [user@cn3144 ~]$ exit salloc.exe: Relinquishing job allocation 46116226 [user@biowulf ~]$
Create a batch input file (e.g. Gctf.sh). For example:
#!/bin/bash module load Gctf Gctf --apix 1.07 --kV 300 --Cs 2.7 --ac 0.1 Micrographs/Falcon*.mrc
Submit this job using the Slurm sbatch command.
sbatch [--cpus-per-task=#] [--mem=#] --gres=gpu:p100:1 --partition=gpu Gctf.sh