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Table 1 Summary of advanced methods studying 3D chromatin interactions and related bioinformatic tools

From: 3D chromatin architecture and transcription regulation in cancer

Technologies Tools Comments
ChIA-PET [294, 295] ChIA-PET Tool: Li et al. [303]
ChiaSig: Paulsen et al. [304]
MICC: He et al. [305]
Mango (also for HiChIP): Phanstiel et al. [306]
ChIA-PET2: Li et al. [307]
ChIAPoP: Huang et al. [308]
ChIA-PET Tool V3: Li et al. [309]
ChIA-PIPE (also for HiChIP): Lee et al. [310]
ChIA-PET tool is the first software package designed for ChIA-PET data analysis
ChiaSig and MICC were developed later, which uses statistical models to adjust random noise
Mango is a bias-correcting pipeline based on statistical confidence, which also corrects bias caused by non-specific interactions due to genomic proximity
Since ChIA-PET tool and Mango are only compatible for half-linker data in the linker trimming step, and ChiaSig and MICC are only a step in the analysis pipeline, ChIA-PET2 was developed, which supports both half-linker and bridge linker data, and integrates all steps required for the analysis
ChIAPoP, which is another fully automated pipeline integrated all the above features and claimed to outperform the above tools
ChIA-PET tool has updated to ChIA-PET tool V3 for updated experimental protocol
ChIA-PIPE is the most comprehensive fully automatic pipeline that integrates many features
HiChIP [300] hichipper: Lareau and Aryee [311]
MAPS: Juric et al. [312]
HiC-Pro: Servant et al. [313]
Fit-HiC: Ay et al. [314]
Juicer: Rao et al. [33]; Durand et al. [315]
HiChIP-Peaks: Shi et al. [316]
FitHiChIP (also for ChIA-PET): Bhattacharyya et al. [317]
cLoops (also for ChIA-PET): Cao et al. [318]
Peakachu (also for ChIA-PET): Salameh et al. [319]
AQuA-HiChIP: Gryder et al. [320]
HiC-DC + : Sahin et al. [321]
ChIA-PIPE used for ChIA-PET data analyses can also be used for HiChIP data analysis
Hichipper and MAPS are designed specifically for HiChIP data processing
One can also use HiC-Pro pipeline for HiChIP data processing, and perform contact calling using Fit-HiC, Mango, and Juicer
HiChIP-Peaks is a peak calling algorithm, which generate satisfactory results for HiChIP data and discover loops
FitHiChIP is a loop calling method, which can also perform differential HiChIP analysis for characterising differential loops
cLoops is another loop calling method using statistical model
Peakachu deploys a random forest classification framework to predict loops
AQuA-HiChIP can perform differential chromatin interaction analysis between samples
ChIA-drop [322]; GAM [323]; SPRITE [324] ChIA-DropBox (ChIA-Drop): Tian et al. [325]
MATCHA (ChIA-Drop and SPRITE): Zhang and Ma [326]
MIA-Sig (ChIA-Drop, GAM, and SPRITE): Kim et al. [327]