image representing the current explore topic

Multimodal Characterization in Mouse Visual Cortex

This dataset includes 4,435 mouse cells from the visual cortex. Available data describe the cells' transcriptomes, intrinsic physiological properties, and  for a subset  morphologies. Based on their transcriptomes, these cells were assigned to one of the 60 transcriptomically defined cell types described in Tasic et al. 2018. Nearly all of the cells are inhibitory, but the dataset includes some excitatory cells as well. Additionally, cells with all three modalities were assigned to one of 28 interneuron met-types that have congruent morphological, electrophysiological, and transcriptomic properties. The definition and analysis of these met-types were introduced in Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells, by Gouwens, Sorensen, et al.

Mouse Patch-Seq VIS Viewer  Publication in Cell    PubMed 33186530

 

 

An example visualization of two GABAergic mouse cells showing their transcriptomic type, MET-type, electrophysiological properties, and reconstructed morphology.

 

 

 

The cells in this dataset come from dissections from several visual areas. The cell metadata file in the Downloads table below provides details for each cell's location.

      

  

How To Use These Data

These data facilitate characterization of the morphological and/or intrinsic electrophysiological properties of neurons belonging to a given transcriptomically defined type of GABAergic interneuron. These data also enable examination of the degree to which distinct transcriptomically-defined types of GABAergic interneurons exhibit morphological and/or intrinsic electrophysiological differences. Lastly, the glutamatergic cells from layer 2/3 facilitate cross-species comparison with the human dataset here.

Currently, researchers' can download the data and analyze in their own systems. Researchers can use the metadata file to find cells of a particular cell type of interest and then use the manifest file to download raw data files for those cells. Instructions and links are below. For an introduction to using these data in that way, there is a video tutorial available that gives an overview of the data and walks through an example Jupyter notebook .

In early 2021, researchers will be able to explore these data on brain-map.org to easily find and compare the cells and cell types based on their morphological, electrophysiological, and transcriptomic properties. The visualization at the top of this page previews this functionality. If you are interested in previewing and testing this functionality before it's released, please post a request in this thread in our Community Forum

 

Downloads

File Description

Cell metadata

Metadata about each cell, including brain structure, donor sex, age, and cell type assignments.

Download Instructions

Instructions on accessing data files, including non-browser methods

Manifest of Raw Data Files for Individual Cells

Manifest of URLs for raw data files for individual cells. Pair with the table of cell metadata to find files for cell types of interest.

Directory of FASTQ files

Neuroscience Multi-omic Data Archive (NeMO) hosts the transcriptomics data files. This online directory in the NeMO Archive hosts the FASTQ files for this dataset. There are 460 GB of total files.

Directory of BAM files

This online directory in the NeMO Archive hosts the BAM files for this dataset. 

Note that the checksum values provided in the file manifest are for the files after they have been extracted from the .tar bundle.

Directory of Gene Expression Matrices

This online directory in the NeMO Archive hosts four gene expression matrices: exons, introns, total counts, and normalized counts.

Note that the checksum values provided in the file manifest are for the files after they have been extracted from the .tar bundle.

Directory of NWB Files

This online directory in Distributed Archives for Neurophysiology Data Integration (DANDI) hosts electrophysiology files.

Note: the Download Instructions above include guidance on downloading these data through the DANDI command line (pip install dandi).

Directory of neuron reconstruction files

This online directory in The Brain Image Library (BIL) hosts neuron reconstruction files.

Note: BIL supports file downloads using several methods, which are detailed in their instructions here.