Final project for BF591—creation of an R Shiny application for various bioinformatics analyses.
BF591 is a course fpcusing on bioinformatic analyses with the R programming language. We develop functions for a wide variety of bionformatic analyses in R.
What the app contains:
Dataset: mRNA-Seq Expression profiling of human post-mortem BA9 brain tissue for Huntington’s Disease and neurologically normal individuals (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE64810).
Sample Information Exploration (samples.R):
Input - Sample Information Table (CSV)
a. Sample Information Summary Table
b. Sample Information Table
c. Sample Information Distribution Plots
Counts Matrix Exploration (counts.R)
Input - Normalized Counts Matrix (CSV)
a. Count Filtering Summary Table
b. Diagnostic Scatterplots
i. Median Count vs. Variance
ii. Medican Count vs. Number of Non-Zero Samples
c. Clustered Heatmap of Counts vs. Samples
d. PCA Biplot of User-Selected PCs
Differential Expression Analysis (diff_expr.R)
Input - Differential Expression Results (CSV)
a. Volcano Plot with User-Select Adjusted P-Value Threshold
b. Table of DEGs with Significant Adjusted P-Value
Gene Set Enrichment Analysis (gsea.R)
Input - FGSEA Results (C2: Canonical Pathway) (CSV)
a. Barplot of Top Pathways by Normalized Enrichment Score (NES)
b. Downloadable Table of Significantly Enriched Pathways
c. Scatterplot of NES vs. -log10(Adjusted P-Value)