GCATemplates available: no
I-TASSER is only for non-commercial use.
Available on Grace only.
I-TASSER (Iterative Threading ASSEmbly Refinement) is a hierarchical approach to protein structure prediction and structure-based function annotation.
module load GCC/9.3.0 I-TASSER/5.1-Perl-5.30.2
The I-TASSER data libraries are in the following directory
Although the I-TASSER libraries (except nr) are updated weekly on the I-TASSER website, the libraries on Grace will be updated at each cluster maintenance.
- example command:
- runI-TASSER.pl -java_home $EBROOTJAVA -runstyle parallel -datadir my_datadir -libdir /scratch/data/bio/i-tasser/5.1 -seqname my_seq_name
- All jobs will be run in parallel on multiple nodes although there may not be a significant reduction in runtime since there are fewer processes than cores on a single node for some I-TASSER scripts.
- When using the parallel runstyle in your runI-TASSER.pl job script, submit your job using 3 tasks and 21GB memory.
- Other scripts such as runCOFACTOR.pl may need more initial tasks but generally each process uses a single-core.
- Each of automatically generated parallel jobs created are hard coded to use 1 core, 7GB memory for 3 days walltime.
- If your job fails due to not enough resources, send a message to the HPRC helpdesk and we will expand the resources for the automatically generated jobs.
- It is possible that your job could fail if you do not have enough SUs to schedule at least 15 single core jobs for 3 days each (1080 SUs)
- example command:
- runI-TASSER.pl -java_home $EBROOTJAVA -runstyle gnuparallel -datadir my_datadir -libdir /scratch/data/bio/i-tasser/5.1 -seqname my_seq_name
- All jobs will be run in parallel on a single-node
- When using the parallel runstyle in your job script, submit your job using 3 tasks and 21GB memory.
- This is the default if you do not specify -runstyle
- Avoid using this mode since it can take 6x longer to run in serial mode.
serial: 1 day 5 hr 22 min gnuparallel: 5 hr 3 min (single-node) parallel: 4 hr 57 min (Slurm; multi-node)