DGAT-onco was designed to detect oncogenes by comparing the mutaitonal profile between cancer population and natural population.

The method is still on progress, please send comments and feedbacks to [email protected]

Operation system: Unix/Linux

python 3 (with os, sys, numpy, pandas, math packagegs installed)

inputfile is a VCF file with the INFO annotated by refGene and dbnsfp33a database through ANNOVAR (http://annovar.openbioinformatics.org/en/latest/)

INFO fields are encoded as a semicolon-separated series of short keys with optional values. Please add gene name(at first field), mutatioin type and patient id before anotating on ANNOVAR:

1 152760163 . G A . . KPRP;Missense_Mutation;TCGA-BH-A0HO-01A-11W-A050-09

After annotation, the vcf will be like:

1 152760163 . G A . . KPRP;Missense_Mutation;TCGA-BH-A0HO-01A-11W-A050-09;...;M-CAP_score=0.005;...

... indicate information omitted here. M-CAP_score is the prior mutation weight we used in analysis. Please put your inputfile file in data folder.

python calculate.py data/inputfile top where inpute file is your file name, top is the number of output

Example: python calculate.py data/BRAC.vcf 50

Result files are:

1. a csv with genes names and coresponding uEMDs.
2. a csv with genes have not results (because they have not corresponding 1000G gene with missense_mutation).