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 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-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] | Â |