Biowulf High Performance Computing at the NIH
Clinical interpretation of genetic variants by the 2015 ACMG-AMP guideline on Biowulf

In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published updated standards and guidelines for the clinical interpretation of sequence variants with respect to human diseases on the basis of 28 criteria. However, variability between individual interpreters can be extensive because of reasons such as the different understandings of these guidelines and the lack of standard algorithms for implementing them, yet computational tools for semi-automated variant interpretation are not available. To address these problems, InterVar generates automated interpretations using 18 out of the 28 criteria to help human reviewers interpret the clinical significance of variants.

References:

Documentation
Important Notes

Interactive job
Interactive jobs should be used for debugging, graphics, or applications that cannot be run as batch jobs.

Allocate an interactive session and run the program. Sample session:

[user@biowulf]$ sinteractive --mem=8g
salloc.exe: Pending job allocation 59748321
salloc.exe: job 59748321 queued and waiting for resources
salloc.exe: job 59748321 has been allocated resources
salloc.exe: Granted job allocation 59748321
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3624 are ready for job
[user@cn3144 ~]$ module load InterVar
[+] Loading InterVar 0.1.7 ...
[user@cn3144 ~]$ InterVar -i $INTERVAR_TEST/ex1.avinput -d $ANNOVAR_DATA/hg19 -o result_hg19
=============================================================================
InterVar                                                                       
Interpretation of Pathogenic/Benign for variants using python scripts of InterVar.
=============================================================================

%prog 0.1.7 20180118
Written by Quan LI,leequan@gmail.com. 
InterVar is free for non-commercial use without warranty.
Please contact the authors for commercial use.
Copyright (C) 2016 Wang Genomic Lab
============================================================================

Notice: Your command of InterVar is ['/usr/local/apps/InterVar/0.1.7/bin/Intervar.py', '-t', '/usr/local/apps/InterVar/DOWNLOADS/intervardb', '--annotate_variation=/usr/local/apps/ANNOVAR/2017-07-16/annotate_variation.pl', '--table_annovar=/usr/local/apps/ANNOVAR/2017-07-16/table_annovar.pl', '--convert2annovar=/usr/local/apps/ANNOVAR/2017-07-16/convert2annovar.pl', '-i', '/usr/local/apps/InterVar/TEST_DATA/ex1.avinput', '-d', '/fdb/annovar/2017-07-16/hg19', '-o', 'result_hg19']

options.table_annovar= /usr/local/apps/ANNOVAR/2017-07-16/table_annovar.pl
...
...
-----------------------------------------------------------------
NOTICE: Multianno output file is written to result_hg19.hg19_multianno.txt
Notice: Begin the variants interpretation by InterVar 
Notice: About 18 lines in your variant file! 
Notice: About 22 variants has been processed by InterVar
Notice: The InterVar is finished, the output file is [ result_hg19.hg19_multianno.txt.intervar ]
=============================================================================
Thanks for using InterVar!
Report bugs to leequan@gmail.com;
InterVar homepage: 
=============================================================================

[user@cn3144 ~]$ exit
exit
salloc.exe: Relinquishing job allocation 59748321
[user@biowulf ~]$

Batch job
Most jobs should be run as batch jobs.

Create a batch input file (e.g. InterVar.sh). For example:

#!/bin/bash
module load InterVar       
InterVar -i $INTERVAR_TEST/ex1.avinput -d $ANNOVAR_DATA/hg19 -o result_hg19

Submit this job using the Slurm sbatch command.

sbatch [--cpus-per-task=#] [--mem=#] InterVar.sh