1. Data from the CHiCAGO paper (Cairns et al., Genome Biology 2016): https://osf.io/nemc6/.
  2. Data from the GWAS-PCHiC integration paper (Javierre et al., Cell 2016): https://osf.io/u8tzp/.
    • Capture design files for the forward and reverse capture
    • CHiCAGO objects for PCHi-C data in each of the 17 human primary cell types
    • Lists of detected interactions across cell types (“peak matrices”)
    • Chromatin annotation of the detected promoter-interacting regions
    • Gene expression data
    • TAD calls
    • GWAS integration data
  3. Data from the PCHi-C analysis of hESC-to-neural differentiation (Freire-Pritchett et al., eLife 2017): https://osf.io/sdbg4/.
    • CHiCAGO objects for PCHi-C data in each of the two analysed cell types
    • Chromatin annotation of the detected promoter-interacting regions
    • Gene expression data
    • TAD calls
  4. Data from the Chicdiff paper (Cairns et al., Bioinformatics 2019): https://osf.io/y9nb5/.
    • A use example for the Chicdiff pipeline
  5. Data from the promoter-connected TFBS variation paper (Mitchelmore et al., NAR 2020): https://osf.io/fa4u7/.
    • List of TF binding affinity CRM variants
    • Association data between TF binding affinity CRM variants and gene expression
  6. Data from the PCHi-C analysis of cohesin- and CTCF-depleted cells (Thiecke et al., Cell Reports 2020): https://osf.io/brzuc/.
    • CHiCAGO objects for each PCHi-C dataset
    • Chicdiff analysis results
    • TAD calls
    • RNA-seq and SLAM-seq data
  7. PCHi-C-based gene prioritisation of COVID-19 GWAS: https://osf.io/k2mxe/.
    • List of prioritised genes
    • Manhattan plots and other visualisations