Ginga is the first step of the CAPOEIRA to bring one step closer personalised oncology. Ginga is a pipeline base on state of the art genomic tools that are seemlesly integrated in a single streamline pipeline. Ginga translates whole exome sequencing (WES) data from patients into a library of specific neoantigens with the goal to create a personalised therapy that its effective at targeting uniquely the cancer cells.
Ginga can output multiple metrics that are key to fully treat and diagnose cancer patients. Ginga outputs 3 main patient specific markers:
- A library of patient specific neoantigens --> These are used in CAPOEIRA's vaccine design to target specifically the cancer cells in the patient using the power of the immune system.
- A library of tumor short DNA sequences containing SNPs --> These short sequences can be found in the blood in the form of ctDNA and can be targeted using CAPOERA's detection system to monitor the effectivity of the vaccine.
- A set of tumor specific chromosomal rearrangements (CR) --> Concentration of CRs found in the ctDNA of the patient can indicate the state of the cancer and if there is relapse.
Ginga was developed in Ubuntu 18.04 LTS and it is meant to be deployed in a Linux based system. It uses multiple establish packages and uses algotrithms code in python to . What you will find in this repository are the python scripts use to streamline the process:
- neoExtract --> Converts the output of the annotated coded amino-acid sequences from Annovar and translate them into short peptides of the form of neoantigens.
- neoSearch --> Ranks the neoantigens according to their binding affinity of MHC-I and retrieves
sudo apt-get install libpng-dev
sudo apt-get install zlib1g-dev
sudo apt-get install libbz2-dev
sudo apt-get install libbz2-dev
- 2018 EPFL IGEM Team
- Daniel Nakhaee-Zadeh Gutierrez