TiRank prioritizes phenotypic niches in tumor microenvironment for clinical biomarker discovery

TiRank is a cutting-edge toolkit designed to integrate and analyze RNA-seq and single-cell RNA-seq (scRNA-seq) data. By seamlessly combining spatial transcriptomics or scRNA-seq data with bulk RNA sequencing data, TiRank enables researchers to identify phenotype-associated regions or clusters. The toolkit supports various analysis modes, including survival analysis (Cox), classification, and regression, providing a comprehensive solution for transcriptomic data analysis.

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Getting Started

• Installation
  • Method 1: Bioconda Installation (Recommended)
  • Method 2: Docker
  • Method 3: Interactive Web Tool (GUI)
• Model Input
  • Requirements
  • Example Data

CLI Tutorials

• Tutorial 1: Spatial Transcriptomics (ST) + Cox Survival Analysis
  • Prerequisites: Download the Model
  • Full Python Script
• Tutorial 2: scRNA-seq + Classification Analysis

GUI Tutorial

• TiRank Web App Tutorial
  • Introduction of TiRank Web
  • Video Tutorial of TiRank Web
  • 1. UploadData
  • 2. Preprocessing
  • 3. Analysis/TiRank
  • 4. Analysis/Differential expression genes & Pathway enrichment

Features Document

• Result Interpretation
• Hyperparameters

API Reference

• API Reference

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Citing & Support

For support, please visit the TiRank GitHub Issues page <https://github.com/LenisLin/TiRank/issues>.

License

TiRank is distributed under the MIT License.