Code accompanying publications from the Tan Lab at Stanford University. The Tan Lab develops and applies single-cell genome structure technologies, including Dip-C (Diploid Chromatin Conformation Capture), to study 3D genome organization in neuroscience, development, and human health.
This repository collects paper-specific analysis scripts that were previously hosted in the tanlongzhi/dip-c repository. The main Dip-C tool and its documentation remain in that repo.
Python 2 scripts for the analysis in the original Dip-C paper:
Tan, Longzhi*; Xing, Dong*; Chang, Chi-Han; Li, Heng; Xie, X. Sunney "Three-dimensional genome structures of single diploid human cells," Science 361, 924-928. DOI:10.1126/science.aat5641 (2018).
This paper introduced the Dip-C method and algorithm for reconstructing 3D diploid genomes from single cells. It studied human B-lymphoblastoid cells (GM12878), peripheral blood mononuclear cells, and mouse embryonic stem cells.
These scripts represent the original standalone workflow before the development of hickit. For the current maintained tool, see the dip-c repository.
R scripts for the multiomics analysis in the fourth Dip-C paper, which introduced Pop-C and vDip-C:
Tan, Longzhi*†; Shi, Jenny*; Moghadami, Siavash; Parasar, Bibudha; Wright, Cydney P.; Seo, Yunji; Vallejo, Kristen; Cobos, Inma; Duncan, Laramie; Chen, Ritchie; Deisseroth, Karl† "Lifelong restructuring of 3D genome architecture in cerebellar granule cells," Science 381, 1112-1119. DOI:10.1126/science.adh3253 (2023).
This paper resolved the first 3D genome structures of single cerebellar cells and created life-spanning 3D genome atlases for both humans and mice. The R scripts here cover multiome analysis using ArchR, LIGER, and Seurat.
- Raw and processed data: PRJNA933352