How to do a correlation analysis between two specific genes across different tissues

Hey everyone!

I am new to the forum and It’s my first time using the Allen mouse brain atlas. I am looking to do an analysis where for each mice within the dataset I would need to extract the data (ISH or 10x) for the expression of two genes (e.g SRD5A1 and AR) across different brain regions and cell types. I am having difficulty understanding how/where would I access the expression data for individual mice within the experiment and then extract the data.

Thank you very much in advance for your help!


Thank you for your question and welcome to the Allen Brain Map Community Forum.

Each 10x port (5K-10K cells) will be from a single mouse, and a single mouse may be used to supply 1-4 10x ports (for ~5K-20K cells from that mouse). Each 10x port is derived from a tissue sample representing a defined ROI (region of interest). Each mouse will have a unique Donor ID in the metadata. The whole 10x dataset is derived from several hundreds of mice.

For the ISH, a single mouse will provide tissue sections for an ISH image series for multiple genes. The same mice did not contribute to the ISH and 10x data.

Hopefully this information addresses your question.

Thank you,


Hey Susan,

Thank you for your response.

So for the 10x dataset, each individual mice contributed some ROI from their brain, but not all of the ones from what would be a whole coronal/sagittal brain slice?

I see. For the ISH data, how would I got about getting the values for two specific genes across the brain for each of the donor mice in the dataset? Would it be necessary to download the whole dataset?

Thank you,


Hi Mika,

I do not quite understand your follow up questions. Could you please clarify?

For your question about the 10x dataset, are you asking if multiple ROIs are ever from one mouse brain?
For your question about the ISH dataset, what values are you referring to in your question?

Thank you,


Hello Susan,

What I am asking is that for the 10x dataset, do all of the mice had their cells derived from the roughly same ROI, as in for example all the mice in the experiment had the cells derived from ROI is in the thalamus, cerebellum, medulla OR is it that one mice had only thalamus and cerebellum while the other cerebellum and medulla but not the thalamus.

For the ISH data, I am referring to the gene expression energy or even better the raw voxel intensity values for a specific gene. For example, If I wanted to see if in the ISH dataset there were 5 male mice and I looked at each of their raw expression data across the sagittal slice for SRD5A1 and AR so then i wanted to analyse if there was correlation between the expression of one and the other, how would I get this data?

Thank you,

Hi MNani,

I believe that the information on the 10X data you are looking for is in the cell metadata csv files we provide. The donor column should tell you want mouse the specific cell came from. The example notebooks I’m linking below will have tutorials on downloading and interacting with this cell metadata.

We have a website and set of tutorials that should help you get started with interacting with the mouse data. You can find them linked here: Mouse whole-brain transcriptomic cell type atlas (Hongkui Zeng) — Allen Brain Cell Atlas - Data Access

The notebooks are also available for you to download and run yourself in this Github repo: GitHub - AllenInstitute/abc_atlas_access: Documentation and examples demonstrating how to access data from the Allen Brain Cell Atlas

I would recommend beginning with the Getting Started notebook as it will attempt to acclimate you to the cache object used to retrieve/serve the data. From there, the general_accessing_10x_snRNASeq_tutorial notebook should provide a way for your to access specific genes from the 10X data in addition to the two part, WMB 10X tutorials. I’m not as familiar with the ISH data we released, however hopefully the example notebooks in the above links will help you to get familiar with the data to the point you can find what you need. Be a bit careful as these are large datasets and you may find yourself out of space if you are downloading them to a personal machine.

Good luck!