Version 4 Update - Fixed bugs and enhanced features

• Improved anndata/txt file conversion to account for prefixes
• Added prefix handling

Comparative Analysis of AAV Serotypes for Transduction of Olfactory Sensory Neurons

Data Description 

Benjamin D.W. Belfort*, Johnathan D. Jia*, Alexandra Garza^, Anthony M. Insalaco^, JP McGinnis, Brandon T. Pekarek, Joshua Ortiz-Guzman, Burak Tepe, Hu Chen, Zhandong Liu, Benjamin R. Arenkiel° 

*,^ These authors contributed equally 

Four male adult mice were exposed to 4 serotypes with nsal lavage. Single nucleus sequencing was performed on the harvested and extrated nuclei from the mouse olfactory epithelium. 4 technical replicates were performed. Data was aligned using STARSolo and the raw count matrix underwent the standard preprocessing steps for scRNAseq data including ambient RNA correction (CellBender), filtering (Scanpy), doublet removal (scvi-Solo), processing, dimensional reduction, batch correction (scvi-scVI), and annotation using canonical markers derived from literature.

This repository contains each of the count matrices from the 4 technical replicates in the form of .txt files. The README file will explain how to use the script to reconstruct the AnnData objects the data was originally extracted from. It also contains the final object containing information such as annotations, Pseudotime values, dimensional reductions, and additional layers including spliced/unspliced counts. The README file also explains how to use the scripts to reconstruct the AnnData object using the .txt files. The prefixes match together.

Zenodo and Github Repo

Johnathan Jia

Email: johnathan.jia@bcm.edu

 Contains Jupyter notebooks and Python scripts used for each step of snRNAseq analysis starting from alignment and quantification to the downstream terminal fate probability using Palantir. All scripts from Github are available in:

Please look in the src/snrna/utils folder to find the scripts to reconstruct the AnnData object.