|
Input data:
1. A
somatic variant summary file of prostate cancer [compiled from Nature
Genetics 44, 685–689 (2012)]
examples/hg19_prostate.txt
Note:
Called variants in Variant Call Format (VCF) are even better in terms of somatic mutations.
Purpose: Identify
cancer-driver somatic mutation, genes and pathways of prostate cancer
Run the commands step by step to see what will happen
1.
(This step is ignored due to lack of
vcf data) Filter by QC and genetic feature (only works for VCF data)
java -jar kggseq.jar --vcf-file XXX.vcf --ped-file
XXX.ped.txt --indiv-pair NonTumor.1:Tumor.1,NonTumor.2:Tumor.2 --out test1
--excel --seq-qual 50.0 --gty-qual 20.0 --gty-sec-pl 50 --gty-dp 8
--gty-af-ref 0.05 --gty-af-het 0.25 --gty-af-alt 0.5 --gty-somat-p 0.05 --genotype-filter
8
2. Annotate
sequence variants by RefGenes:
java -jar kggseq.jar --annovar-file
examples/hg19_prostate.txt --out test1 --excel --db-gene
refgene --gene-feature-in 0,1,2,3,4,5,6,7
3. Predict
driver somatic-mutations and genes of cancers
java -jar kggseq.jar --annovar-file
examples/hg19_prostate.txt --out test1 --excel --db-gene refgene --gene-feature-in
0,1,2,3,4,5,6,7 --db-score dbnsfp --cancer-driver-predict all --filter-nondisease-variant
4. Predict
cancer driver biological pathways
java -jar kggseq.jar --annovar-file
examples/hg19_prostate.txt --out test1 --excel --db-gene refgene --gene-feature-in
0,1,2,3,4,5,6,7 --db-score dbnsfp --cancer-driver-predict all
--filter-nondisease-variant --pathway-db cura
5. Annotate
sequence variants COSMIC somatic and OMIM information
java -jar kggseq.jar --annovar-file
examples/hg19_prostate.txt --out test1 --excel --db-gene refgene --gene-feature-in
0,1,2,3,4,5,6,7 --db-score dbnsfp --cancer-driver-predict all
--filter-nondisease-variant --pathway-db cura --cosmic-annot
--omim-annot
6. Prioritize
sequence variants by candidate genes with protein interaction
information
java -jar kggseq.jar --annovar-file
examples/hg19_prostate.txt --out test1 --excel --db-gene refgene --gene-feature-in
0,1,2,3,4,5,6,7 --db-score dbnsfp --cancer-driver-predict all
--filter-nondisease-variant --pathway-db cura --cosmic-annot --omim-annot --candi-list
NKX3,PTEN,TP53 --ppi-annot string --ppi-depth 1
7. Prioritize
sequence variants by candidate genes with pathway information
java -jar kggseq.jar --annovar-file
examples/hg19_prostate.txt --out test1 --excel --db-gene refgene --gene-feature-in
0,1,2,3,4,5,6,7 --db-score dbnsfp --cancer-driver-predict all
--filter-nondisease-variant --pathway-db cura --cosmic-annot --omim-annot --candi-list
NKX3,PTEN,TP53 --ppi-annot string --ppi-depth 1 --pathway-annot cura
8. Prioritize
sequence variants by PubMed
java -jar kggseq.jar --annovar-file
examples/hg19_prostate.txt --out test1 --excel --db-gene refgene --gene-feature-in
0,1,2,3,4,5,6,7 --db-score dbnsfp --cancer-driver-predict all
--filter-nondisease-variant --pathway-db cura --cosmic-annot --omim-annot
--candi-list NKX3,PTEN,TP53 --ppi-annot string --ppi-depth 1
--pathway-annot cura --pubmed-mining-gene prostate+cancer
|