Skip to content
/ aespca Public

Code to reproduce Adaptive elastic-net sparse PCA for robust cross-species, cross-platform analysis of complex gene expression data in Alzheimer’s disease (Hin et al.)

Notifications You must be signed in to change notification settings

nhihin/aespca

Repository files navigation

Comparison of brain transcriptomes from 5XFAD mice, fAD-like zebrafish, and human early-onset as well as late-onset sporadic Alzheimer's disease

  • Workflow in R using AESPCA to explore and compare brain transcriptomes across various species in Alzheimer's disease contexts.

  • For more details, please see Chapter 5: Adaptive elastic-net sparse PCA for robust cross-species, cross-platform analysis of complex gene expression data in Alzheimer’s disease in my thesis (https://digital.library.adelaide.edu.au/dspace/handle/2440/129610, p.165 onwards).

About

Code to reproduce Adaptive elastic-net sparse PCA for robust cross-species, cross-platform analysis of complex gene expression data in Alzheimer’s disease (Hin et al.)

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages