Home

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The Home part is the intronduction page for this website. It introduces our analysis, for example,from the picture below,you can get the information that we integrated heart relatived data from six studies; the total single cells are around 250w; data comes from 7 heart regions; we have used more than 10 methods to analysis our data; the main disease we research is cardiomyopathy.

Data Viewer

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The Data Viewer may take dozens of seconds to load due to the substantial volume of data present in the Heart Cell Atlas.

The Data Viewer page features the UMAP that presents the sample characteristics and gene expressions in the Heart Cell Atlas. From the "Subclusters" tab, you can choose to view a particular UMAP from three subtypes, VCM,FB,EC. Then, select a study from the "Data Names" tab and click on the "Submit" button:

The left panel plot is a plotly.js module that displays the integrative UMAPs of the different diseases, different samples, regions and races in the Heart Cell Atlas.

(1) By scrolling down the selection from "Color By", you can view coloured cells from a certain attribute for the cells. Several other dimiensions to view the UMAP are described as below: A list of selectable attributes to display the UMAPs are shown in the left column.

(2) On the right panel you can view the expression of a certain gene on the UMAP from search.

(3) You may download the UMAP, using selection tools to crop an area and zoom-in/out by clicking on the tool bars on the top-right of the panel (Some tools may take several seconds to load).

Analysis

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These part include our some analysis results for you to read or download.

Differential Expression

For this part, we split three cell type data into three gourp,DCM-HCM,DCM-Healthy and HCM-healthy to do gene differential expression analysis.So you should first choose a compare group and a cell type to get the results. Do not forget to click submit.

After you choose and click submit. The results will show below. You can also download the csv file by click the download button if you need.
(1) The genes column shows the gene names for differential genes.
(2) The second column shows the Deseq2 log2foldchange values for every gene.
(3) The Third column shows the Deseq2 p-adj values for every gene.
(4) The Modelcoeff shows the GLM coeff values for every gene.
(5) The Modelpadj shows the adjusted pvalues of every gene.We do it by Benjamini & Hochberg method.
(6) The Exp column shows the gene expression levels within two compare groups, eight high or low in one group compare with another.

WGCNA

We do WGCNA analysis for three cell types,VCM,FB and EC. For every cell type,we get different gene modules and we check the model siginificance by linear model. You can choose a cell type and than choose a module to see result. Do not forget to submit your chosen.

The left part of the result shows the box plot of the ME values of current module. The right part of the result shows linear model and Tukey test P values.You can download module genes by click download button.

Scenic

We do Scenic analysis similar to the gene differential analysis. You can get the results just like the differential gene analysis, choose a compare group , choose a cell type and submit. As for the Scenic result. The left part is a heatmap of significant TFs. The right part is a table shows the TF expression levels in compare groups and support a button to download regulon genes.

Group Analysis

When we do group analysis, we first split our data into three cell types,VCM,FB and EC. Than we group every cell type data accoring to pseudotime of EF values. After data has been grouped, we use a geneset score method to get the score of some GO and KEGG pathways. Beseids, we also get the gene expression change pattern according to our groups. So for this part, you shold first choose a group method and than choose a cell type before you get the result.

The left part of the result shows the term change pattern according to the group method and cell type you choose. The right part of the result shows the gene pattern.

Cell Chat

For this part, choose a compare group just like other analysis and than choose a reults to see Cellchat result.

Dataset

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This page offers the processed data we do all the analysis.