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Author: gaow

index.md

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 # ColocBoost Manuscript Resources
 
 Code and data to reproduce figures in ColocBoost manuscript.
+
+
+## About ColocBoost
+
+ColocBoost is a statistical approach for identifying shared genetic influences across multiple traits and molecular phenotypes. By leveraging statistical learning techniques to detect colocalization patterns, our method offers improved statistical power and biological interpretation compared to traditional approaches.
+
+## Repository Structure
+
+This Jupyter Book contains the codes and data used to generate all figures from our manuscript. Each notebook is fully executable and documented to ensure reproducibility of our results. The main sections include:
+
+- **Figure 2**: Method overview and benchmark comparisons
+- **Figure 3**: Cell-type specific xQTL colocalization analyses
+- **Figure 4**: Evidence of colocalization across traits
+- **Figure 5**: Variant prioritization and functional characterization
+- **Figure 6**: Application to disease-relevant loci
+
+## Getting Started
+
+To navigate this resource, use the table of contents in the left sidebar. Each figure section contains interactive notebooks that allow you to:
+
+1. View the code used to generate analyses
+2. Examine data associated with the figures
+3. Reproduce visualizations
+
+## Computational Requirements
+
+The analyses in this book were performed using:
+- R version 4.1 or higher
+- Key R packages: data.table, ggplot2, dplyr
+