Welcome to scVMAP’s documentation!

A comprehensive platform for integrating single-cell chromatin accessibility regions with causal variants.

scVMAP database access link: https://bio.liclab.net/scvmap/

scVMAP is a user-centric database that offers intuitive workflows, customizable parameters, and comprehensive data accessibility, featuring:

1. Integrates causal variants with chromatin accessibility regions at single-cell resolution.

2. Includes data from 183 scATAC-seq samples and 15,884 fine-mapping datasets.

3. Encompasses over 3,876,800 effective trait-sample pairs, 26.3 million trait-cell type pairs, and 32.1 billion trait-cell pairs.

4. Performs enrichment analysis for traits across specific cells or cell types.

5. Identifies relevant genes and transcription factors (TFs), and performs pathway enrichment analysis for these genes in the context of specific samples and traits.

6. Constructs an integrated regulatory network (variant-TF-gene) linking traits to samples.

7. Offers comprehensive resources for data download.

8. Makes the code for reproducing the database workflow publicly available.

9. Publishes the full-stack development code for the web application.

10. Provides API interfaces for programmatic data access.

Cite

Zheng-Min Yu, Feng-Cui Qian, Qiao-Li Fang, Xiang-Yang Meng, Yan-Yu Li, Chen-Chen Feng, Li-Dong Li, Bing-Long Li, Yu-Rong Feng, Hui Jiang, Qiu-Yu Wang, Xuan Fan, Jin-Cheng Guo, Chun-Quan Li, scVMAP: a comprehensive platform for integrating single-cell chromatin accessibility regions with causal variants, Nucleic Acids Research, Volume 54, Issue D1, 6 January 2026, Pages D1270–D1280, https://doi.org/10.1093/nar/gkaf1112

Contents

• 1. scVMAP process
  • 1.1 Data processing methods
  • 1.2 Data collection and curation
    • 1.2.1 Collection of scATAC-seq data
      • 1.2.1.1 scATAC-Ref
      • 1.2.1.2 scBlood
      • 1.2.1.3 GreenleafLab
      • 1.2.1.4 PlaqView
      • 1.2.1.5 Summary
    • 1.2.2 Collection of trait data
      • 1.2.2.1 FINEMAP
      • 1.2.2.2 SuSiE
      • 1.2.2.3 Summary
  • 1.3 Variant-function-mapping at single cell resolution
    • 1.3.1 g-chromVAR
    • 1.3.2 SCAVENGE
    • 1.3.3 Code for using scVMAP
      • 1.3.3.1 Install R packages
      • 1.3.3.2 Download files
      • 1.3.3.3 Create formatted directories
      • 1.3.3.4 Execute command
  • 1.4 Differential gene activity and pathway enrichment analysis across cell types
    • 1.4.1 Differential activity genes of cell types
    • 1.4.2 Gene pathway enrichment analysis
• 2. scVMAP usage
  • 2.1 Home
    • 2.1.1 Trait or disease search
    • 2.1.2 Single cell sample search
    • 2.1.3 Gene search
    • 2.1.4 TF search
    • 2.1.5 Variant search
  • 2.2 Data-browse
    • 2.2.1 Single cell chromatin accessibility data
      • 2.2.1.1 Granularity: Sample ID
      • 2.2.1.2 Granularity: Cell type
    • 2.2.2 Trait or disease data
      • 2.2.2.1 FINEMAP
      • 2.2.2.2 SuSiE
  • 2.3 Search
    • 2.3.1 Search information by category or source cohort
      • 2.3.1.1 Category
      • 2.3.1.2 Source cohort
    • 2.3.2 Search information by tissue type or cell type
      • 2.3.2.1 Tissue type
      • 2.3.2.2 Cell type
    • 2.3.3 Search information by gene
    • 2.3.4 Search information by TF
    • 2.3.5 Search information by SNP
  • 2.4 Detail
    • 2.4.1 Overview
      • 2.4.1.1 scATAC-seq
      • 2.4.1.2 Fine-mapping result
    • 2.4.2 TRS
      • 2.4.1.1 The first part
      • 2.4.1.2 The second part
    • 2.4.3 Differential genes
    • 2.4.4 Trait-relevant genes
    • 2.4.5 Gene hub network
    • 2.4.6 Differential TFs
    • 2.4.7 Trait-relevant TFs
    • 2.4.8 TF hub network
    • 2.4.9 Integrated network
  • 2.5 Analysis
    • 2.5.1 Analyzing variant-to-function mapping
    • 2.5.2 Analyzing variant-to-function mapping with genes
    • 2.5.2 Analyzing variant-to-function mapping with TFs
    • 2.5.4 Comparative analysis between samples or traits
  • 2.6 Statistics
    • 2.6.1 Visualization
    • 2.6.2 Display
  • 2.7 Download
    • 2.7.1 Download TRS data for each sample
      • 2.7.1.1 Overview of scATAC-seq data: txt file
      • 2.7.1.2 scATAC-seq data: H5AD file
      • 2.7.1.3 The result data of method g-ChromVAR: H5AD file
      • 2.7.1.4 The result data of method SCAVENGE: H5AD file
    • 2.7.2 Download fine-mapping result data for each sample
      • 2.7.2.1 Overview of fine-mapping result data: xlsx file
      • 2.7.2.2 Fine-mapping result data
    • 2.7.3 Download other data
      • 2.7.3.1 Fine-mapping result data: tar.gz file
      • 2.7.3.2 Differential gene data: txt file
      • 2.7.3.3 Differential TF data: txt file
      • 2.7.3.4 MAGMA result data: tar.gz file
        • 2.7.3.4.1 Annotation: txt file (After decompression)
        • 2.7.3.4.1 Gene analysis -raw data: txt file (After decompression)
      • 2.7.3.5 HOMER result data: tar.gz file
      • 2.7.3.6 Gene enrichment analysis results: tar.gz file
        • 2.7.3.6.1 Gene enrichment for differential genes
        • 2.7.3.6.2 Gene enrichment results of traits (hg19/hg38)
      • 2.7.3.7 Gene regulation/V2G annotation data:
        • 2.7.3.7.1 Common SNP: txt file (After decompression)
        • 2.7.3.7.2 eQTL: txt file (After decompression)
        • 2.7.3.7.3 Risk SNP: txt file (After decompression)
        • 2.7.3.7.4 Enhancer (SEA v3): txt file (After decompression)
        • 2.7.3.7.5 Enhancer (SEdb v2): txt file (After decompression)
        • 2.7.3.7.6 Super enhancer (dbSUPER): txt file (After decompression)
        • 2.7.3.7.7 Super enhancer (SEA v3): txt file (After decompression)
        • 2.7.3.7.8 Super enhancer (SEdb v2): txt file (After decompression)
        • 2.7.3.7.9 3D chromatin interaction: bed file (After decompression)
        • 2.7.3.7.10 MPRA: csv file
  • 2.8 Contact
  • 2.9 On-line analysis
• 3. scVMAP API
• 4. Development environment
• 5. FAQs (Frequently Asked Questions)
  • 5.1 Discovering issues on the website
  • 5.2 There is a problem accessing the website
  • 5.3 Publicize front-end and back-end code
  • 5.4 Difficulties encountered in searching for trait or disease data