ASCETIC API and Shiny App

marcoxa commented 10 months ago

Background

By leveraging the ever-increasing availability of cancer omics data and the continuous advances in cancer data science and machine learning, we have discovered the existence of cancer (sub)type-specific evolutionary signatures associated with different disease outcomes. These signatures represent "favored trajectories" of driver genes acquisition that are repeatedly detected in patients with similar prognosis. The Agony-baSed Cancer EvoluTion InferenCe (ASCETIC) is a novel framework that extracts such signatures from NGS experiments generated by different technologies such as bulk and single-cell sequencing data (cfr., [1]).

Goal

The goal of the the project is to design an API to the ASCETIC analysis pipeline and to develop a dedicated Shiny App with enhanced data processing, interaction and visualization capabilities.

Difficulty Level: Medium

The difficulty of the project is twofold: first of all the developer will have to fully understand the ASCETIC pipeline, both from the machine learning and the mathematical perspectives. Secondly, the developer will have to design an API that will ease the ASCETIC use, in addition with a new easy-to-use Shiny App. The App will take as input raw (DNA or RNA) sequencing data and will provide as output interactive models of cancer evolution, and the stratification of patients in prognostically significant clusters, related to the discovered evolutionary signatures. Results will be delivered both in a easy-to-understand graphical fashion, and in file formats complaint to other data analysis pipelines.

Size and Length of Project

Size

The project size is medium: 175 hours.

Length

Timeline is flexible and the project is 12 weeks

Skills

Essential skills: R, understanding of machine learning and mathematical models.
Nice to have skills: knowledge of Bioconductor distribution

Public Repository

The current repository is: ASCETIC. A new one will probably be needed in the future.

References

Fontana, D., et al., Nat Commun 14 (2023)

Potential Mentors

Alex Graudenzi, alex.graudenzi@unimib.it
Daniele Ramazzotti, daniele.ramazzotti@unimib.it
Marco Antoniotti, marco.antoniotti@unimib.it

divyansh169 commented 9 months ago

Hello @marcoxa @khanspers I am interested in contributing to this issue as I am compatible with this tech stack and currently learning about the project. Can you please guide where to ask project related queries?

khanspers commented 9 months ago

NRNB has been accepted as a mentoring organization for GSoC 2024. The contributor application period is March 18 – April 2. Here are some useful links:

GSoC contributor guide NRNB project proposal template Eligibility requirements Full program timeline

luke-estes commented 7 months ago

Hello my name is luke, I have 2 years experience with R and have some experience and interest in working phylogenies. how would I go about joining the team?

khanspers commented 6 months ago

This is an active GSoC 2024 project. Closing this project idea as it is no longer available to other contributors.

nrnb / GoogleSummerOfCode