Student Work
Utilizing Cloud Computing for the Statistical Analysis of Large-Scale Genomic Data
公开 DepositedThe 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
- 最新修改
- 2024-05-17
关系
- 属于 Collection:
项目
单件
缩略图 | 标题 | 公开度 | Embargo Release Date | 行动 |
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yakovenkoDistProcessingFinalReport.pdf | 公开 | 下载 | |
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distProcessing_0.zip | 公开 | 下载 |
Permanent link to this page: https://digital.wpi.edu/show/b2774087q