CMap_iLINCS

Evaluating gene–compound relationships across multiple platforms can be challenging. CMap_iLINCS integrates public data sources and provides workflows to analyze your experimental data alongside them.

##Data Sources This workflow incorporates data from:

• Connectivity Map (CMap) – connectivity data with knock-down, over-expression, compound, and compound class signatures
• iLINCS – gene expression profiles and perturbation signatures
• SwissTargetPrediction – target predictions for compounds of interest

##Features

• Retrieve and analyze signatures, gene expression profiles, and compound target predictions
• Compare how compound signatures align or contrast (e.g., pro-coagulant vs. anti-coagulant compounds)
• Generate heatmaps, correlation plots, and upset plots at the gene and pathway level
• Combine experimental findings (e.g., RNA-seq results, gene–phenotype associations) with public resources for a meta-analysis approach

##Usage

• Main functions are available in CMap_iLINCS_SwissTarget_functions.R
• Each folder includes data from relevant databases and example R scripts to explore compound signatures
• The script iLINCS_cMAP_SwissTargetPredictions_combinedHeatmaps.R enables combining data from the aforementioned platforms and your experimental findings

##Applications

• Identify candidate genes and drugs for further investigation
• Generate data-driven hypotheses for experimental validation
• Explore opposing compound actions (e.g., therapeutic vs. adverse effects)

⚠️** Note: ** Figures and outputs do not provide definitive answers. They are intended as exploratory tools to guide hypothesis generation.

##Future Directions

• Implement as R Markdown documents or Shiny apps for interactive use
• Enable API/HTML/cURL queries to directly access data from external platforms