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Using CATlas

Browse datasets

1. Navigate to the "Browse" Page:

   Go to the "Browse" page to access single-cell datasets.

2. Select Datasets:

   Use the checkboxes in the sidebar to filter and select datasets based on different species and sequencing methods.

3. Access Dataset Details and Downloads:
   • Click the [Details] button to view more detailed information about the selected datasets.
   • Click the [Download] button if you want to download processed data.
   OR
   • Click the [Explore] button to visualize epigenetic signal tracks, cell browser and 3D genome conformation, depending on the dataset types.

Browse Datasets Explanations

1. "Visualization of Epigenetic signal tracks"

   • Select Cell Types:
     • Add or remove cell types using the multi-select list below the [Class] section.
   • Tracks Panel:
     • Datatypes: Click on the desired datatype to toggle its inclusion.
     • Merged: Select this option to merge tracks by cell types or by data types.
     • Log-transformed: Toggle whether to apply a log transformation to BigWig tracks.
   • Cell Names and Colors:
     • List cell type names and their default colors as stored in CAtlas.
   • Load Public Tracks
     • Click the button to manage the inclusion of SNP tracks (for human) and JASPAR tracks (for human, mouse, and fly).






2. "Visualization ofCell browser "to view cell clusters via the UCSC Cell Browser

   Visualization of Cell Clusters and Gene Activity:

   Click view -> split view -> go to "gene" panel

   



3. "Visualization of 3D genome conformation":

   • Select only one cell type.
   • Click the [hic contact] button to load HiC tracks into the Integrated Genome Viewer (IGV).
   • Use drag and drop within the IGV to visualize different genomic regions.
   
   
   

Search dataset or cell types

• Search Dataset

  Enter a species name (e.g., human, mouse) and use the fuzzy autocomplete feature to select a specific dataset. Once selected, you will be directed to the epigenetic signal tracks page.

  



• Search Cell Types

  
  
  
• Single Cell Type Search: If the input cell type has only one record in CAtlas, the system will display signal tracks for that specific cell type.
  
  
  
• Multiple Cell Types Search: If the input cell type has multiple records in CAtlas, a table will list all matching cell types. Please click on the rows in this table and then click the [VISUALIZATION] button to proceed to the cell types track page.

  Cell Type Visualization Page

  
  
  
  
  

Predict regulatory codes via Deep Learning Models

Overview of Deep Learning Models

We have trained Basenji models ( Kelley DR, Reshef YA, Bileschi M, Belanger D, McLean CY, Snoek J. Sequential regulatory activity prediction across chromosomes with convolutional neural networks. Genome Res. 2018 May;28(5):739-750. doi: 10.1101/gr.227819.117. Epub 2018 Mar 27. PMID: 29588361; PMCID: PMC5932613) on >1,700 cell types/states, with a focus on snATAC-seq datasets. For each model, we applied grid-search to find the optimal hyperparameters, benchmarked the performance on predictions, and tested for robustness across multiple training processes.

Make Predictions

Based on a variety of user queries, CATlas can utilize these models to predict the potential function of CREs in different cell types/states, prioritize putative TF binding sites, interpret the function of non-coding risk variants, visualize results, and deliver prediction outcomes to users via email.

• For Genome Regions Analysis

  1. Input a task name for your analysis (default: "default").
  2. Select a species of interest.
  3. Select a dataset for model-based analysis.
  4. Modify the cell types input to add or delete cell types, limit to 6.
  5. Input a prediction length (default: 200).
  6. Specify the chromosome range (e.g., "chr1, start, end").
  7. Input your email to receive results.
  8. Click the "Run Analysis" button.

• For Genome Variant Analysis (Human Only)

  1. Follow the same first five steps as in the genome regions analysis.
  2. Input specific genomic variants (e.g., "rs657666:C>T").
  3. Follow the same last two steps as in the genome regions analysis.

This analysis may take several minutes. After completion, users can directly view the results online.

Prediction Results Page

• For Genome Regions

  CATlas will display both the true signals and predicted signals on queried genomic regions for selected cell types. Please use the track control panel for more display options. In silico saturation mutagenesis results are listed below, formatted in Plotly, allowing for dynamic interaction.

  • For each track in IGV, the label "" at the top represents the experimental coverage, while the "_predicted" below depicts the predictions made by Basenji.

  • Explanations for "Plotly for analysis result "

    1. The first row of the seq logo plot shows the summed minimum (loss) change among possible substitutions.
    2. The second row represents the summed maximum (gain) change.
    3. The third row of line plots illustrates both the minimum (loss) and maximum (gain) changes among possible substitutions.
    4. In the fourth row of the heatmap, the quantities displayed indicate the change in Basenji prediction 'Δ pred' (summed across the sequence) following the substitution of the nucleotide specified in each row.
  
  
  
  
  

• For Genome Variants

  Similar to the genome region analysis, with the mutation site marked by a red dashed line.

  • For each track in IGV, the label "" at the top represents the experimental coverage, while the "_predicted" below depicts the predictions made by Basenji.

  • Explanations for "Plotly for analysis result "

    1. The first row of the seq logo plot displays the summed change among possible substitutions based on the pre-mutated nucleotide.
    2. In the second row of the heatmap, the quantities shown indicate the change in Basenji prediction 'Δ pred' (summed across the sequence) following the substitution of the nucleotide specified in each row.
    3. The third row of the seq logo plot illustrates the summed change among possible substitutions based on the post-mutated nucleotide.
    4. In the fourth row of the heatmap, the quantities displayed represent the change in Basenji prediction 'Δ pred' following the substitution of the specified nucleotide in each row.
  
  
  
  
  

Download prediction results

• Via Email

  The user will receive an email with the job ID, website link for visualization, and prediction results in the attached file.
  Please unzip the attached file, check the “report.pdf”, and explore prediction results in corresponding directories.

  
  
  

• Online

  The analysis results will be kept online for three months. Users can retrieve and visualize the results via JOBID labeled in email.