Customprodbj is a Java-based tool for customized protein database construction:
- Build a customized database based on single VCF file.
- Build a customized database based on multiple VCF files from a sample.
- Build a customized database based on multiple VCF files from multiple samples.
Please download Customprodbj program from the release page: https://github.com/wenbostar/customprodbj/releases
java -jar customprodbj.jar
-d mRNA fasta database
-f A file which includes multiple samples. This parameter is used to
build a customized database for
-h Help
-i Annovar annotation result file. Multiple files are separated by
','.
-o Output folder
-p1 The prefix of variant protein ID, default is VAR_
-p2 The prefix of final output files, default is merge
-r Gene annotation data
-ref Output reference protein database file
-t Whether or not to add reference protein sequences to the output
database file
-v Verbose
Step 1: Variant annotation using ANNOVAR:
perl table_annovar.pl test.vcf annovar_database/humandb/ -buildver hg19 -out out/test -protocol refGene -operation g -nastring . -vcfinput --thread 30 --maxgenethread 30 -polish
java -jar customprodbj.jar -i test.hg19_multianno.txt -d annovar_database/humandb/hg19_refGeneMrna.fa -r annovar_database/humandb/hg19_refGene.txt -t -o out/
The input file "test.hg19_multianno.txt" is from ANNOVAR annotation result. The input files "annovar_database/humandb/hg19_refGeneMrna.fa" and "annovar_database/humandb/hg19_refGene.txt" are two files used by ANNOVAR. Before uses do variant annotation using ANNOVAR, users need to download these files using ANNOVAR. Please follow the instruction described here: http://annovar.openbioinformatics.org/en/latest/user-guide/download/.
Step 1: Variant annotation using ANNOVAR:
Perform variant annotation for each VCF file using the same method described in above section.
java -jar customprodbj.jar -f input_variant_file_list.txt -d annovar_database/humandb/hg19_refGeneMrna.fa -r annovar_database/humandb/hg19_refGene.txt -t -o out/
The format of input_variant_file_list.txt looks like below:
sample somatic germline rna msi
sample1 s1a.hg19_multianno.txt s1b.hg19_multianno.txt s1c.hg19_multianno.txt s1d.hg19_multianno.txt
Please note the columns are separated by "\t".
Step 1: Variant annotation using ANNOVAR:
Perform variant annotation for each VCF file using the same method described in above section.
java -jar customprodbj.jar -f input_variant_file_list.txt -d annovar_database/humandb/hg19_refGeneMrna.fa -r annovar_database/humandb/hg19_refGene.txt -t -o out/
The format of input_variant_file_list.txt looks like below:
sample somatic germline rna msi
sample1 s1a.hg19_multianno.txt s1b.hg19_multianno.txt s1c.hg19_multianno.txt s1d.hg19_multianno.txt
sample2 s2a.hg19_multianno.txt s2b.hg19_multianno.txt s2c.hg19_multianno.txt s2d.hg19_multianno.txt
sample3 s3a.hg19_multianno.txt s3b.hg19_multianno.txt s3c.hg19_multianno.txt s3d.hg19_multianno.txt
The final outputs consist of three files:
*-varInfo.txt: A table contains the detailed amino acid change information. Each row is a variant.
*-var.fasta: Customized protein database.
*-varStat.txt: Summary data.
Wen, B., Li, K., Zhang, Y. et al. Cancer neoantigen prioritization through sensitive and reliable proteogenomics analysis. Nature Communications 11, 1759 (2020). https://doi.org/10.1038/s41467-020-15456-w