dangdachang
I‘m a Ph.D cnadiate of bioinformatics and focus on the study of computer programming, 3D Genomics
China
Pinned Repositories
ConsTADs
Topologically associating domains (TADs) have emerged as basic structural and functional units of genome organization, and have been determined by many computational methods from Hi-C contact maps. However, the TADs obtained by different methods vary greatly, which makes the accurate determination of TADs a challenging issue and hinders subsequent biological analyses about their organization and functions. This project is about comparing different TAD-calling methods, building the TAD separation landscape and finding the consensus TADs from results of multiple methods.
dcHiC
dcHiC: Differential compartment analysis for Hi-C datasets
diHMM-cpp
Improved implementation of diHMM in C++
hic-data-analysis-bootcamp
Workshop on measuring, analyzing, and visualizing the 3D genome with Hi-C data.
HiC_data
A (continuously updated) collection of references to Hi-C data. Predominantly human/mouse Hi-C data, with replicates.
HiC_tools
A collection of tools for Hi-C data analysis
IC-Finder
Segmentations of HiC maps into hierarchical interaction compartments
ImputeHiFI
ImputeHiFI: an imputation method for single-cell multiplexed DNA FISH data by utilizing single-cell Hi-C and RNA FISH data
machine-learning-notes
This is the notes of the way of machine learning study. You may find something useful in it.
scHiC_notes
Notes on single-cell Hi-C technologies, tools, and data
dangdachang's Repositories
dangdachang/ConsTADs
Topologically associating domains (TADs) have emerged as basic structural and functional units of genome organization, and have been determined by many computational methods from Hi-C contact maps. However, the TADs obtained by different methods vary greatly, which makes the accurate determination of TADs a challenging issue and hinders subsequent biological analyses about their organization and functions. This project is about comparing different TAD-calling methods, building the TAD separation landscape and finding the consensus TADs from results of multiple methods.
dangdachang/dcHiC
dcHiC: Differential compartment analysis for Hi-C datasets
dangdachang/diHMM-cpp
Improved implementation of diHMM in C++
dangdachang/hic-data-analysis-bootcamp
Workshop on measuring, analyzing, and visualizing the 3D genome with Hi-C data.
dangdachang/HiC_data
A (continuously updated) collection of references to Hi-C data. Predominantly human/mouse Hi-C data, with replicates.
dangdachang/HiC_tools
A collection of tools for Hi-C data analysis
dangdachang/IC-Finder
Segmentations of HiC maps into hierarchical interaction compartments
dangdachang/ImputeHiFI
ImputeHiFI: an imputation method for single-cell multiplexed DNA FISH data by utilizing single-cell Hi-C and RNA FISH data
dangdachang/machine-learning-notes
This is the notes of the way of machine learning study. You may find something useful in it.
dangdachang/scHiC_notes
Notes on single-cell Hi-C technologies, tools, and data
dangdachang/scHiCluster
dangdachang/scHiCPTR
Unsupervised pseudotime inference through dual graph refinement for single-cell Hi-C data
dangdachang/scKTLD
A python package for identifying TAD-like domains on single-cell Hi-C data
dangdachang/ShiArthur03
dangdachang/STAGE
dangdachang/TADGATE
TADGATE is a computational tool to TADGATE to identify TADs in Hi-C contact map with a graph attention autoencoder.
dangdachang/Transcription