Section 1 : View the Database

 Hi-C, high-throughput chromatin conformation capture (3C), is one of the most-widely used genome-wide molecular assay that can identify long-range chromatin interactions. To visualize the structure for a Hi-C data, follow the steps below

Click on Browse Menu in the navigation bar to load the full list of the Hi-C datasets. OR Click on the Get Started button on the homepage. Both are highlighted below

Section 2 : Search the Database

GSDB provides two ways to search the database
1) GSDB provides a summary of the information provided in the database through a Summary Pane. By clicking on a property/item in the Summary, the user can search the database for all the Hi-C data containing this property.

- Example

The image below shows the Result when the user clicks on 100KB in the Resolution Summary Pane


2) Users can search the database by Typing the keywords about the Filename,Title of Hi-C data, Hi-C data Resolution, Project Hi-C data was generated from,Project ID, and the GEO_Accesion_No in the Search Pane highlighted in red below

- Example

The image below shows the Result of search for 1MB Resolution Hi-C data

Section 3 : Visualization of Chromosome 3D Structure

STEP 1 : Click on the View link in the 3D Structure Column to view the details and structures for a Hi-C data.

- Output

The image below shows the Result when a user clicks on the View link for the GM12878 dataset in Row 1 above.

The Red Highlight section shows the infromation about the Resolution(s) available for the Hi-C data.

The Blue Highlight section displays the structure available for the Hi-C data.

The Green Highlight section shows the Evaluation result available for the Hi-C data. It displays the Spearman Correlation between the output structure and the input Hi-C data, and other evaluation result obtained.

STEP 2 : Select the Algorithm, Dataset , Chromosome, and Click on the Display button to view the structure on the viewer.

- Example

The image below shows the result when a user selects Algorithm = LorDG, Dataset = GM12878, Resolution = 1MB, Chromosome = 1.

Section 4 : Download the Chromosome 3D Structure

Click on the Download link in the "3D Structure Column" to download the 3D structures for the different algorithms available for a Hi-C data.

- Output

When the user clicks on the Download link a compressed .tar.gz file with the Data file Name will be downloaded.

Section 5 : Download the Normalized Hi-C Data

Click on the Download link in the "Normalized Hi-C Data Column" to download the Normalized Hi-C Data used to generate strcutures for the different algorithms.

- Output

When the user clicks on the Download link a compressed .tar.gz file with the Data file Name will be downloaded.

Section 6 : Structure Evaluation

GSDB provides two ways to evaluate a structure
1) Compare chromsosome structure in pdb format with input Interaction Frequency(IF) matrix

To compare with IF matrix, user needs to provide the following inputs:

Select Interaction Frequency(IF) Matrix option as Type of Input file 1

Provide a link to a IF matrix or upload the IF matrix file from computer

Provide a link to a chromosome structure in pdb format or upload the structure file from computer

Click on the Compare button to compute the genome or chromsome evaluation

IF Matrix Format: The data format allowed for the IF matrix is a comma-seperated or a tab-seperated n by n symmetrix matrix. Where n is the number of regions/bins in the IF Matrix

- Example

Click on the Sample Inputs, IF Matrix Sample input for Input file 1 and Structure Sample input to use them for evaluation.

- Result

On clicking the Compare button , the user gets the prompt below about the evaluation result

2) Compare a chromsome structure with another chromsome structure in pdb format

To compare two structures, user needs to provide the following inputs:

Select Chromosome structure in PDB format option as Type of Input file 1

Provide a link to a Chromosome structure or upload the Structure file from computer

Provide a link to a another Chromosome structure or upload the Structure file from computer

Click on the Compare Button to compute the genome or chromsome evaluation

- Example

Click on the Sample Inputs, Structure Sample input for Input file 1 and Structure Sample input to use them for evaluation.

- Result

On clicking the Compare button , the user gets the prompt below about the evaluation result

Section 7 : Computational requirement and performance

The GSDB chromosome structure generation was done on two server machines: a x86_64 bit Redhat-Linux server con-sisting of multi-core Intel(R) Xeon(R) CPU E7-L8867 @ 2.13GHz with 120 GB RAM and a high-performance computing cluster (Lewis) with Linux. Using a high-performance computing (HPC) cluster machine, we allocated 10 cores, 80G of memory, with a time limit of 2 days for each chromosome structure reconstruction task per algorithm. No structures are avilable for chromosome Hi-C data that took more than two days to be constructed by an algorithm. Find more details about Lewis Cluster here

Section 8 : References

Wang, S., Xu, J. and Zeng, J., 2015. Inferential modeling of 3D chromatin structure. Nucleic acids research, 43(8), pp.e54-e54.

Varoquaux, N., Ay, F., Noble, W.S. and Vert, J.P., 2014. A statistical approach for inferring the 3D structure of the genome. Bioinformatics, 30(12), pp.i26-i33.

Zhu, G., Deng, W., Hu, H., Ma, R., Zhang, S., Yang, J., Peng, J., Kaplan, T. and Zeng, J., 2018. Reconstructing spatial organizations of chromosomes through manifold learning. Nucleic acids research, 46(8), pp.e50-e50.

Rieber, L. and Mahony, S., 2017. miniMDS: 3D structural inference from high-resolution Hi-C data. Bioinformatics, 33(14), pp.i261-i266.

Zhang, Z., Li, G., Toh, K.C. and Sung, W.K., 2013. 3D chromosome modeling with semi-definite programming and Hi-C data. Journal of computational biology, 20(11), pp.831-846.

Zou, C., Zhang, Y. and Ouyang, Z., 2016. HSA: integrating multi-track Hi-C data for genome-scale reconstruction of 3D chromatin structure. Genome biology, 17(1), p.40.

Lesne, A., Riposo, J., Roger, P., Cournac, A. and Mozziconacci, J., 2014. 3D genome reconstruction from chromosomal contacts. Nature methods, 11(11), p.1141.

O. Oluwadare; Y. Zhang; J. Cheng. A maximum likelihood algorithm for reconstructing 3D structures of human chromosomes from chromosomal contact data, BMC Genomics, 19:161, 2018 [at BMC Genomics]

T. Trieu, J. Cheng. 3D Genome Structure Modeling by Lorentzian Objective Function. Nucleic Acids Research, accepted, 2016. [at NAR]

B. Adhikari, T. Tuan, J. Cheng. Chromosome3D: Reconstructing Three-Dimensional Chromosomal Structures from Hi-C Interaction Frequency Data using Distance Geometry Simulated Annealing. BMC Genomics, 17:886, 2016. [at BMC Genomics]

T. Tuan, J. Cheng. MOGEN: a tool for reconstructing 3D models of genomes from chromosomal conformation capturing data. Bioinformatics, accepted, 2015. doi: 10.1093/bioinformatics/btv754. [at BMC Bioinformatics]

Rosenthal, M., Bryner, D., Huffer, F., Evans, S., Srivastava, A. and Neretti, N., 2018. Bayesian Estimation of 3D Chromosomal Structure from Single Cell Hi-C Data. bioRxiv, p.316265.