GSE279254 Processing Pipeline
RNA-Seq
code_examples
1 step
Publication
Tissue-resident memory CD8 T cell diversity is spatiotemporally imprinted.Nature (2025) — PMID 39843748
Dataset
GSE279254Tissue-resident memory CD8 T Cell Diversity is Spatiotemporally Imprinted [snRNA-Seq]
Warning: Pipeline descriptions and code snippets may be inferred or AI-generated. Use them only as a starting point to guide analysis, and validate before use.
Processing Steps
Generate Jupyter Notebook-
1
cellranger was used to process the raw sequencing files to generate count matrices per cell
Cell Ranger vNot specified$ Bash example
# Install Cell Ranger (example for version 7.1.0) # wget https://cf.10xgenomics.com/releases/cell-ranger/cellranger-7.1.0.tar.gz # tar -xzf cellranger-7.1.0.tar.gz # export PATH=/path/to/cellranger-7.1.0:$PATH # Example: Download a human transcriptome reference (e.g., GRCh38-2020-A) # mkdir -p /path/to/references # wget -O /path/to/references/refdata-gex-GRCh38-2020-A.tar.gz https://cf.10xgenomics.com/releases/cell-ranger/refdata-gex-GRCh38-2020-A.tar.gz # tar -xzf /path/to/references/refdata-gex-GRCh38-2020-A.tar.gz -C /path/to/references # Define variables SAMPLE_ID="my_sample" FASTQ_DIR="/path/to/raw_fastqs" TRANSCRIPTOME_REF="/path/to/references/refdata-gex-GRCh38-2020-A" # Run cellranger count to generate count matrices cellranger count \ --id=${SAMPLE_ID} \ --transcriptome=${TRANSCRIPTOME_REF} \ --fastqs=${FASTQ_DIR} \ --sample=${SAMPLE_ID}
Raw Source Text
cellranger was used to process the raw sequencing files to generate count matrices per cell Assembly: mm10 Supplementary files format and content: "h5ad" file containing combined total nuclei profiled from all mice and regions of the gastrointestinal tract