input

Instructions to obtain processed Seurat objects

The processed data are available on Zenodo and can be downloaded by visiting the project repository web page. Once on the web page scroll down and select download for the file(s) of interest.

Alternatively, use wget in a terminal to retrieve the data:

wget https://zenodo.org/record/11979927/files/eq_synovial_fluid_annotated.rds  # Full synovial fluid dataset
wget https://zenodo.org/record/11979927/files/eq_synovial_fluid_myeloid_annotated.rds  # Myeloid dataset
wget https://zenodo.org/record/11979927/files/eq_synovial_fluid_tcell_annotated.rds  # T cell dataset
wget https://zenodo.org/record/11979927/files/eq_synovium_annotated.rds  # Full synovium dataset

Prefer to use tools in python or R? Check out zenodo_get or inborutils to download within the respective software.

Example usage of zenodo_get

Below is the code needed to install zendo_get using pip and the command to download the repositiry specific to this project (this should be completed in an environment with python3 installed).

Visit the zendo_get page for most up to date instructions.

#install the python tool using pip
pip3 install zenodo_get

#download the Zenodo repository
zenodo_get 10.5281/zenodo.11979927

Instructions to obtain count matrices from NCBI GEO

To download via command line, navigate to directory in which you wish to download the data and run the following:

#pull down the data
wget https://ftp.ncbi.nlm.nih.gov/geo/series/GSE254nnn/GSE254840/suppl/GSE254840_RAW.tar

#unpack the tar ball
tar -xvf GSE254840_RAW.tar

To download via NCBI webpage, navigate to the GSE254840 page and download the zip folder containing the count matrices. Once downloaded, you will likely need to extract/unpack the data before using (should be able to do by right clicking on the GSE254840_RAW.tar file).

Instructions to obtain raw data from SRA

Navigate to directory of interest and run for each file you wish to pull down. Then with SRA toolkit installed run:

NOTE: all raw data files are around 1TB of data

prefetch -v --max-size=55000000 SRR #smallest file for ex
fastq-dump --gzip --split-files SRR

From there you will have to modify the file names to be compatible with the Cell Ranger input (if using Cell Ranger). It expects:
[Sample Name]_S1_L00[Lane Number]_[Read Type]_001.fastq.gz

Feel free to reach out (email or create an issue on GitHub) if you have trouble getting the data downloaded.