Student Work
Utilizing Cloud Computing for the Statistical Analysis of Large-Scale Genomic Data
Público DepositedConteúdo disponível para baixar
open in viewerThe 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.
- Creator
- Publisher
- Identifier
- E-project-050124-182411
- 122350
- Advisor
- Year
- 2024
- Date created
- 2024-05-01
- Resource type
- Major
- Source
- E-project-050124-182411
- Rights statement
- Última modificação
- 2024-05-17
Relações
- Em Collection:
Itens
Itens
Miniatura | Título | Acesso | Embargo Release Date | Ações |
---|---|---|---|---|
yakovenkoDistProcessingFinalReport.pdf | Público | Baixar | ||
distProcessing_0.zip | Público | Baixar |
Permanent link to this page: https://digital.wpi.edu/show/b2774087q