MungeSumstats: a Bioconductor package for the standardization and quality control of many GWAS summary statistics
Murphy, A. E., Schilder, B. M. & Skene, N. G. Bioinformatics 37, 4593–4596 (2021)
CV
Education
- Ph.D in Computational Biology, Brain Sciences, Imperial College London, 2025 (expected)
- M.S. Bioinformatics and Computational Genomics, Queen’s University, 2020
- B.S. Management Science and Information Systems, Trinity College Dublin, 2017
Experience
- PhD Brain Sciences - UK Dementia Research Institute Neurogenomics Lab, Imperial College London (current)Undertaking a PhD with Dr. Nathan Skene in the UK DRI Neurogenomics Lab at Imperial College London. My PhD is based around the predicting cell type-specific, regulatory effects of genetic variants in neurodegenerative diseases with a primary focus on Alzheimer’s disease. Supervised numerous masters and undergraduate students across a broad range of computational biology projects including genetics, statistical analysis and machine learning.
- Research Assistant - UK Dementia Research Institute Neurogenomics Lab, Imperial College London (2021)Undertook a bioinformaticians role working under Dr. Nathan Skene in the UK DRI Neurogenomics Lab at Imperial College London. My role included the development of novel pipelines for the analysis of these differing omic types along with the development of computational genomic tools and associated R packages for submission to Bioconductor.
- Research Assistant - Overton Group, Queen’s University Belfast (2020)Expanded on the research from my master’s thesis, developing a systems biology, machine learning framework to uncover the instigated molecular players in differing biological contexts. Created a multi-purpose, run time and memory efficient R package and applied the framework to multi-omic data from differing cellular processes and disease states. Utilised parallel computing functionality, a high performance compute cluster and advanced machine learning methodologies including one-class classification. This was coupled with prior biological knowledge through known interactions from pathway databases. Also investigated the biological relevance of the uncovered molecular networks in the differing states through network biology approaches.
- Data Analytics Consultant - Pricewaterhouse Coopers (PwC) (2017)Led multiple projects across a wide variety of engagements. An experienced manager, with the ability to get the best results from the team under pressing timelines. A technical approach, using advanced analytical techniques, married with an understanding of the business’s needs has been proven in all engagements. Practiced in completing all aspects of data analytics pipelines from investigation, ETL, cleansing, analysis, modelling, insight and the development and deployment of automated solutions. Tangible results for projects including correcting over €30 million worth of loans that were in arrears in one of Irelands largest banks and increasing the success rate of targeted enforcement in a public sector body by over 15%.
- Data Analyst - Aon Centre for Innovation and Analytics (ACIA) (2016)Gained real-world experience in data analytics, decision making and applied statistics as well as developing an understanding of best practice project management. Undertook projects to design, develop and implement an in-house skills matrix system for senior management, giving insights into employee utilization and predicting possible future skill shortages.
Selected Publications
A balanced measure shows superior performance of pseudobulk methods in single-cell RNA-sequencing analysis
Murphy, A. E. & Skene, N. G. Nat. Commun. 37, 7851 (2022)
Avoiding false discoveries in single-cell RNA-seq by revisiting the first Alzheimers disease dataset
Murphy, A. E., Fancy, N. & Skene, N. G. eLife 12:RP90214 (2023)
Teaching
Awards
- The Genetics Society Conference ECR Grant Scheme (2023)
- The Guarantors of Brain travel grant (2023)
- Prize for Computational Reproducibility in Dementia Research, UK DRI (2022)