We took advantages of neural network methods and developed an in silico method, AIVAR (Artificial Intelligent VARiant classifier), which is highly comparable to human experts on known data sets.
20/08/26 Added supplementary tables of the AIVAR paper https://doi.org/10.1093/bioinformatics/btz442, the original file depository is no longer available.
1.Download the AIVAR package to any directory.
2.Dowload external tools
python 3.x required packages: argparse,numpy,keras,h5py
perl 5.2x:
3.Download database
Required databases are deposited under the example dirctory, or use the links provided below for direct download：
Notes: don't forget to give the paths to the above database files specified in bin/database.cfg
4.Prepare Input Data
The input data for AIVAR is the annotated output file of the variants.Please use ANNOVAR and the relative annotation databases for variant annotations.
ANNOVAR usage to generate required variant annotations for input to AIVAR：
Usage：
$ table_annovar.pl --vcfinput example.vcf database/hg19 -out example_out -buildver hg19 -remove -protocol refGene,1000g2015aug_all,1000g2015aug_eas,1000g2015aug_afr,1000g2015aug_amr,1000g2015aug_eur,1000g2015aug_sas,hrcr1,cg69,gnomad_genome,exac03,esp6500siv2_all,esp6500siv2_aa,esp6500siv2_ea,gnomad_exome,ljb26_all,intervar_20170202,dbnsfp31a_interpro,dbscsnv11,avsnp147,tfbsConsSites,wgRna,targetScanS,gwasCatalog,eigen -operation g,f,f,f,f,f,f,f,f,f,f,f,f,f,f,f,f,f,f,f,r,r,r,r,f -nastring . --onetranscript
the annotation output file example_out.hg19_multianno.txt is the input file for AIVAR
5.How to run
We strongly recommend going through the example/ directory where you can view commands and example input file formats required for running.
command-line：
$ python3 AIVAR.py --help
arguments:
-h, --help show this help message and exit
-t TYPE, --type TYPE
Please specify analysis module to be used: AIVAR model generation or variant pathogenicity prediction,required
-i INPUT, --input INPUT
Please specify ANNOVAR annotation results, required
-o OUTPUT, --output OUTPUT
Please specify output file ,required
-c CATEGORIZE, --categorize CATEGORIZE
Please specify class file containing pathogenicity classification for each variant in the training set (only required for AIVAR model generation),optional
-m MODEL, --model MODEL
Please specify AIVAR model to be used,optional
Building an AIVAR model
We have a ready-to-use model (trained already) under the directory: bin/AIVAR.model_weights.h5
Users can also build their own AIVAR model
Usage：
$ python3 AIVAR.py -t model -i example.hg19_multianno.txt -c example.class -o example
-t choose type of analysis module, in this case 'model'
-i annotation output file from ANNOVAR（see 4.Prepare Input Data）
-o the output filename
-c class file, a 1-column text file containing pathogenicity classification (0 for benign/likely benign and 1 for pathogenic/likely pathogenic) of each variant in the ANNOVAR output file (number of labels has to match with the number of variants); the column has a header line named '#class'
class file like:
#class
0
1
0
0
1
1
0
0
0
1
1
0
1
...
Using AIVAR model to predict variant pathogenicity
usage：
$ python3 AIVAR.py -t predict -i example.hg19_multianno.txt -o example -m example.model_weights.h5
-t choose type of analysis module, in this case 'predict'
-i annotation output file from ANNOVAR（see 4.Prepare Input Data）
-o the output filename
-m the AIVAR model to be used for prediction（default：bin/AIVAR.model_weights.h5）
AIVAR is free for non-commercial use without warranty.