Gene Set Clustering based on Functional annotation
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Updated
May 3, 2024 - Perl
Gene Set Clustering based on Functional annotation
From functional enrichment results to biological networks
A collection of source codes for network-based multi-omics analysis using integrated genome-wide association studies (GWAS) and transcriptomic data to identify genetic contribution into lithium response in patients with bipolar disorder (BD).
util scripts for various omics data analysis
A Python script for testing over- and under-representation of Gene Ontology (GO) terms in a target gene set relative to a background set, using the hypergeometric test with Benjamini-Hochberg FDR correction.
RNA-seq analysis of FOXP1-regulated genes in a mouse hippocampus model with integration of schizophrenia GWAS data
Comprehensive RNA-seq differential expression analysis with automated Snakemake workflow, tool-specific Conda environments, and publication-style visualizations.
Context-aware restriction of the Gene Ontology (GO) for enrichment analysis.
Interactive ATAC-seq peak analysis app in R Shiny—annotation, motif enrichment, machine learning, and more. Singularity/HPC ready.
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