Transcriptomic analysis on Shiny

Purpose

Its aim is to simplify the analysis from mouse/cell clutured samples, which are often a small size. In detailed, the number of sample is limited below 52, due to it hosted on a server with poor resource :(

Also, due to the resource limitation, password is required for analysis. The password is stored in Pwd.rds using a simple string object. To be honest, this approach only deters honest people but not those with ill intentions. However, it does have some effect in conserving lab resources.

Install

You can simply download all the file, and run using RStudio, or host it on Shiny Server.

Before run it, please check dependency.R to make sure every package depended on is installed properly.

Features & Modules Description

Differential Expression Analysis Module (DEGAnalysis)

• Basic quality control and filtering (e.g., protein-coding genes and non-protein-coding genes)
• Differential analysis of bulk RNA-seq (using DESeq2, edgeR, limma)
• Differential analysis of non-sequencing source data, such as microarrays or other sources (using limma)
• PCA analysis
• Correlation analysis between samples
• Sequence trend clustering analysis (Mfuzz analysis)
• Batch effect correction for samples from different sources (using sva)

Sample Scoring Analysis Module (MatAnalysis)

• Pathway activity inference (PROGENy model)
• Transcription factor activity inference (CollecTRI model)
• ssGSEA scoring analysis
• Includes multi-databases from MsigDB
• Immune infiltration scoring (using xCell)

Correlation Analysis Module (CorrAnalysis)

• Expression correlation analysis between a single gene and all other genes

Co-expression Module Identification (coExprAnalysis)

• Identification of gene groups based on non-negative matrix factorization (powered by ultra-fast RcppML package)

• We don't adopt WGCNA for its slow calculation, because the limited resource of server.

Enrichment Analysis Module (GSEAAnalysis)

• Enrichment analysis via clusterProfiler, supports ORA, multi-group ORA, and GSEA.

• Because hosted on server, KEGG support is solved by gson package.

Version

Version: 0.1.2 (2024-8-17)