Canadian Centre for Computational Genomics (C3G) - Montreal node

Mentors: Student: abstatic

<p>SegAnnDb (Segmentation Annotation Database) is a web app, which helps researchers analyze a chromosome profile for copy number alterations in genes. Many studies have found that copy number variations are linked to diseases like - cancer, tumors, Alzheimers etc. Study and analysis of CNVs is an active area of research in bioinformatics.</p> <p>SegAnnDB allows users to upload a profile and then annotate it on basis of <code>loss</code>, <code>gain</code>, <code>deletion</code>, and <code>amplification</code> Various profiles are stored in the webapp and researchers can work with them. SegAnnDB provides most accurate results when compared to other applications. It uses concepts of machine learning and data analysis to arrive at most accurate models.</p> <p>The aim of this project is to add various significant features into SegAnnDB , some of these will be -</p> <ul> <li>Test Suite</li> <li>Permissions System on profiles</li> <li>Replace large PNGs by sub regions of chromosome</li> <li>Faster Deletion of profiles</li> <li>Sharing of annotations </li> <li>Safe cleaning of generate log files</li> <li>Packaging it as docker container</li> </ul> <p>This project will greatly improve collaboration on SegAnnDB, it will also make its development easier and more people will start using it in their research and analysis.</p>

Mentors: Student: Tushar Dubey

<p>The goal of this project is to implement additional steps in the tumor_pair pipeline in order to integrate Structural Variant detection in the analysis. Tools like Lumpy,Delly,SCoNEs and PopSV would be integrated as part of this project to extend the tumor_pair pipeline to include analysis of Structural variants like deletions, tandem duplications, inversions and translocations and also the estimation of Copy Number variation.</p>

Mentors: Student: wlong799

<p>Interpreting genomic data largely relies on simulation software. One important family of software simulates population-level diversity over the course of evolution as a function of selection and demography. The ∂a∂i open-source package, developed by Ryan Gutenkunst (<a href="http://gutengroup.mcb.arizona.edu" target="_blank">http://gutengroup.mcb.arizona.edu</a>), is the leading software in the field, but is limited when handling large datasets.</p> <p>This project aims to overhaul the computational engine of the ∂a∂i software by implementing a recently developed approach for solving partial differential equations. The project will use ∂a∂i's interface and code-base, but introduce a new spectrum simulation engine. Using a moment-based approach will improve performance and reduce numerical uncertainty, offering the genetics community with a general-purpose simulation tool that can address larger and more complex datasets than previously possible.</p> <p>A prototype version of the computational engine is already running. The goal of this project will be to optimize the engine and embed it efficiently in the existing code-base.</p>