1.1. Overview

HHCDB provides users with two search interfaces: Tissues name and Cells/Cell lines search. Users can enter the identification factor, sample type, gene symbol, chromatin location, GO ID,KEGG ID to obtain the corresponding heterochromatin region information through the drop-down menu. It should be noted that the identification factor and sample type must be filled in. After clicking “Search”, the relevant information will be displayed in an intuitive tabular format. Users can download the information of the table by clicking the button “Download the CSV file”at the bottom of the table.

The HHCDB provides a set of advanced analysis and visual interaction tools for the acquired heterochromatin region, including:

(1) UCSC Genome Browser

(2) Visualization of enrichment of transcription factors,transposons,3D genome and CpG islands

(3) SingleCell-Plot (only for tissue sample)

(4) KEGG enrichment analysis

(5) GO enrichment analysis

Figure 1-1. Overview of whole Search

Figure 1-1-2. Overview of whole Search

1.2. UCSC Genome Browser

Users can select any row in the table, click “update UCSC,” and access the UCSC Genome Browser interface to obtain the corresponding genomic information.Each time a different row in the table is selected, it is necessary to click “update UCSC” again to refresh and obtain the corresponding information.

Figure 1-2. UCSC Genome Browser

1.3. Visualization of enrichment of transcription factors, transposons,3D genome ,super enhancers, Dnase I and CpG islands

Transposable elements, CpG islands, 3D genomics, super enhancers, Dnase I and peaks associated with heterochromatin regions can be displayed by self-developed visualization tools. The user can click on any row in the table and click “Show” in the Visualization to get the visualization. Users can also view the information on the left and right sides of the area by filling in the value and clicking “Show”. Regionally enriched transposable elements and transcription factor information is presented in a separate table below. Each time the user changes the row that needs to be viewed, they need to re-click show.

It is important to note that the user must first select a line in order to proceed to the next action.

Figure 1-3. Visualization of enrichment of transcription factors, transposons and CpG islands

1.4. SingleCell-Plot

The user can obtain TSNE,UMAP plot of cell annotation about, as well as the violin plots, TSNE, UMAP plots of the interested gene enriched in the heterochromatin region by clicking on any row in the table and clicking show in the SingleCell-plot. The user can obtain information about the transcription factors, transposons, CpG islands, etc. enriched in the heterochromatin region by clicking on any row in the table and clicking show in the Visualization.

Figure 1-4. SingleCell-Plot

1.5. KEGG enrichment analysis

Users can click “Run” to obtain the KEGG enrichment analysis results for the retrieved data and adjust the parameters of the enrichment analysis using a slider to obtain different visualizations. Users who want to download the result data and PDF file need to first click the “Refresh” button. Moreover, users can also change the size of the images in the obtained PDF file by entering the desired length and width.It is important to note that the user must first click the “Refresh” button to get the pdf file.

Figure 1-5. KEGG enrichment analysis

1.6. GO enrichment analysis

Users can click “Run” to obtain the GO enrichment analysis results for the retrieved data and adjust the parameters of the enrichment analysis using a slider to obtain different visualizations. Users who want to download the result data and PDF file need to first click the “Refresh” button. Moreover, users can also change the size of the images in the obtained PDF file by entering the desired length and width.It is important to note that the user must first click the “Refresh” button to get the pdf file.

Figure 1-6. GO enrichment analysis

2.1. Overview

Figure 2-1. Overview of analysis

2.2. cancer-associated heterochromatin regions

In the <cancer-associated heterochromatin regions>, corresponding the genomic information,GO ID and KEGG ID, associated with cancer-specific heterochromatin regions can be displayed in an intuitive tabular format. The genomic distribution of cancer-specific heterochromatin regions can also be displayed. Users also have the flexibility to customize the input box by selecting cancer type, identifying factor, tumor sample and normal sample, respectively.

Figure 2-2. cancer-associated heterochromatin regions

2.3. Prognosis and enrichment analysis of differentially expressed genes associated with cancer-specific heterochromatin regions

In the <differantial heterochromatin genes in cancer> interface, corresponding the genomic information,GO ID and KEGG ID, associated with differential heterochromatin genes can also be displayed in an intuitive tabular format.Users also have the flexibility to customize the input box by selecting cancer type, identifying factor, tumor sample and normal sample, respectively.

HHCDB also provides several analysis to explore the importance of heterochromatin gene,including:

HHCDB provided independently Differential Heterochromatin Region Analysis Platform (DFRAP) which developed a differential heterochromatin identification algorithm to identify differential heterochromatin regions. A user-friendly analysis interface was provided to help users to identify cancer-specific heterochromatin regions and explore the importance of cancer-specific heterochromatin genes. Users have the flexibility to customize the input box by selecting cancer type, identifying factor, tumor sample and normal sample, respectively. There are three interfaces including <cancer-associated heterochromatin regions>,<differantial heterochromatin genes in cancer> and <cancer non-Heterochromatin differential gene TF regulatory network>.

(1) Venn diagram

(2) association alaysis of cancer clinical features(survival,T,N,M,stage)

(3) immune infiltration analysis

(4) construction of drug-gene network

(5) construction of PPI netwrok

Figure 2-3. Overview of differential heterochromatin genes in cancer

Figure 2-4. Venn diagram of differential heterochromatin genes and differential expression gene of corresponding cancer

Figure 2-5. cancer clinical features analysis

Figure 2-6. immune infiltration analysis

Figure 2-7. construction of drug-gene network

Figure 2-8. construction of PPI network

2.9. cancer non-Heterochromatin differential gene TF regulatory network

Specifically, for cancer non-heterochromatin genes(normal sample is heterochromatin,whereas cancer sample is non-heterochromatin), genomic information, GO and KEGG id will be displayed in an intuitive tabular format.What’s more,transcription factor regulatory network can also be constructed. Users also have the flexibility to customize the input box by selecting cancer type, identifying factor, tumor sample and normal sample, respectively.

Figure 2-9. construction of TF-gene network

HHCDB provides two tools, one is cancer survival analysis and the other is cancer immune cell infiltration analysis.

Figure 3-1. Kaplan Meier survival analysis

Figure 3-2. Immune infiltration analysis

4.1. Download processed data

HHCDB provides information on heterochromatin regions of tissues and cells/cell lines, cancer-specific heterochromatin regions, and single-cell datasets used by HHCDB on the download page.

Figure 4-1. Overview of download

Figure 4-1. Download processed data

Figure 4-2. Download heterochromatin region of tissue sample

Figure 4-3. Download heterochromatin region of cell/cell line sample

Figure 4-4. Download cancer differential heterochromatin region

Figure 4-5. Download single cell dataset information