Tutorial

  • #Browse Data
  • #Data Viewer
  • #Spatial Analysis
  • #Analyze Your Spatial Omics Data
Browse Data
Find the entry to view all datasets
There are two ways to view datasets in Aquila. You can view all the dataset at once. Or by publications.
Find your interesting datasets
After you enter the dataset page, you can search, filter, or sort to find the dataset that you want.
  • Search: You can search by any keywords or search by marker or gene name.
  • Filter: Use the filter panel below to select the conditions.
  • Sort: You can sort by number of cells/markers/ROI, year or publications.
What's in the data card?
For each dataset, You are presented with a data card containing lots of information related to this data.
Download the datasets
You can click on the download button on the data card to download one dataset. To download multiple datasets, add the dataset to the download list. Once you select enough datasets, click the download list button, and confirm to proceed.
View the data
Click on the view button to view the dataset.
Perform spatial analysis

Feel free to run all kinds of analysis including advanced spatial analysis. If you don't know what each parameter mean, it's ok to stick with defaults. Or check the for reference. Click on theRUNto run the analysis, the visualization will be automatically shown or updated.

Good to go!
Now that you got some idea on how to use Aquila, you may want to run those analysis on your own data. Gladly, this is made available in analysis section. Check next tutorial part for details. Keep going!
Data Viewer
What each section do?
  • Data summary section: Information related to the dataset.
  • Select ROI: You can switch between different ROIs.
  • ROI Preview: Visualize the spatial distribution of cells and expression.
Select an ROI
Click the view to select an ROI. This ROI is then added to the ROI preview panel and the following ROI visualization panel. Delete the unwanted ROI if you add many ROIs in the ROI preview panel.
Cell Map
When you select an ROI, here is where you view its details. You can click the legend item to mute a particular cell type. Use the two sliders to adjust the point size and canvas size.
Expression Map
You can select multiple markers and view their expressions at the same time. An expression distribution profile is presented for you. This work similarly with ROI panels.
Markers Co-localization
As a mocking visualization of experiments like IF or FISH, you can visualize more than one marker in one ROI by mixing different colors.
Spatial Analysis
Analysis panel
You can select different analyses on the left side panel. Notice that some analysis is locked at first because they require the information from step `Find Neighbors`. After embedding the neighbor network, the locks are gone. If you found other analyses unavailable, some analyses rely on cell type information, which is missed in the dataset.
Prompts in analysis

You likely have no idea what an analysis does. Hence, we provide you with a brief introduction to each analysis. Click on the expand arrow to view the details of each analysis. You can hover on theto get a tip if you don't know what a parameter does. Don't want to mess with your brain? Stick with default values is always great.

Run the analysis

Click on theRUNto run the analysis, the visualization will be automatically shown or updated.

Analyze Your Spatial Omics Data
Prepare 3 files
You need to prepare 3 files to run the analysis. They should all have headers and the same number of lines representing cells. Currently, we only support 2D data. Support for 3D data is on its way!
  1. ROI file: Each line annotates the ROI that the cell belongs to.
  2. Cell info file: Must have at least 2 columns, coordination X and coordination Y, or you can add an extra column to specify cell type.
  3. Expression file: Each column is a gene, and the header is the gene name.
Specify a Data ID
Although a random Data ID is generated for you, it's highly recommended that you put a meaningful name instead of a meaningless Data ID. In case you don't remember the content of that data a few days later. Click the start to run the analysis.
Run the analysis
Click START to start processing your file, it may take a while. A status bar would show you which step is currently on. Every data is saved on your local computer for your data privacy! The analysis record will never get expired if you don't delete it. But if you clear your browser cache. It will be disappeared. Be careful!
Check your result
When the processing is finished, you should be about to see the newest one from the records and open it to run analysis freely on your dataset. The usage is the same as any other datasets in Aquila.
What does each analysis do?

CELL TYPE

Simple statistics on the proportion of different cell types

CELL TYPE

Simple statistics on the density of different cell types

CELL TYPE

The expression correlation between two or more markers

NEIGHBORS

The correlation between two or more markers expression at cells neighbors

CELL TYPE

Few functions can be used profile the distribution of different cells at different distance range

CELL TYPE

There are three patterns

1) Random

2) Cluster: Cells are aggregated together

3) Evenly distributed: This is very common to see

You can know whether two cells are neighbors to each other, in the visualization, two cell will be linked if they are neighbors

NEIGHBORS

Using graph community detection algorithms to cut the graph into different communities.

CELL TYPE

NEIGHBORS

Calculate different centrality metrics based on neighbor graph

CELL TYPE

NEIGHBORS

This is to determine the spatial interaction between two cell type, either association or avoidance. Association means they are likely to appear at each others neighborhood mostly. Notice that we use a permutation method here, the results are NOT deterministic.

CELL TYPE

Useful to evaluate the heterogeneity within a tissue

NEIGHBORS

Value close to -1 and is significant indicate negative spatial auto-correlation and vice versa.

NEIGHBORS

If a gene is spatial variable, it suggest that spatial factor has certain influence on it's expression