Utilizing Cloud Computing for the Statistical Analysis of Large-Scale Genomic Data

Yakovenko, Taisiia

Student Work

Utilizing Cloud Computing for the Statistical Analysis of Large-Scale Genomic Data

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The project focuses on proposing a novel p_GFisher computation, which is a modification of standard GFisher statics calculation, to determine novel genes associated with Amyotrophic Lateral Sclerosis (ALS). The proposed Python implementation is based on an existing R code base both of which rely on singular machine processing. The continuation of the project would entail extending p_GFisher Python implementation to support distributed computation by following the proposed pipelines connecting Hail and PySpark to processing larger genetic VCF files.

This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

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