|
| Status |
Public on Feb 19, 2024 |
| Title |
spleen tissue no treatment (NT) |
| Sample type |
SRA |
| |
|
| Source name |
House mouse
|
| Organism |
Mus musculus |
| Characteristics |
cells: spleen cells no treatment
|
| Treatment protocol |
No treatment (WT/NT), PHZ and serial bleeding (BLD)
|
| Growth protocol |
Spleen tissue were isolated from mice under steady state, 5 days post PHZ treatment and 5 days after the first serial bleeding.
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Cells were washed, and processed using the 10x Genomics Chromium controller and Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 following manufacturer's instructions.
The library was prepared using 10xGenomics's Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 and dual index kit following manufacturer's instructions. Illumina P5 and P7 sequences and sample index sequences are added during the Sample Index PCR. The final library fragments contain the P5, P7, Read 1 and Read 2 sequences used in Illumina bridge amplification and sequencing. Additionally, each fragment contains the 10x Barcode, UMI and cDNA insert sequence used in data analysis. Sequencing was done by DNBseq platform at BGI Genomics.
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
DNBSEQ-G400 |
| |
|
| Data processing |
Raw reads were aligned to the pre-build mm10 reference genome using cellranger count v7.0.0 (10X Genomics) with default settings.
The molecule information files were combined using cell ranger aggr with --normalize=none --nosecondary options.
The R package Seurat v4.1.1 was used for downstream analysis.
Cells with UMI counts less than 500, fewer than 100 genes detected, or ≥ 7% of reads mapped to mitochondrial genes were removed.
Read counts were normalized using the Seurat SCTransform function with the option vst.flavor=“v2”.
Variation due to mitochondrial RNA ratio and cell cycle phase scores were regressed out.
The data were integrated based on the 3,000 most highly variable genes using the Seurat integration procedure.
Principal component analysis was performed using the Seurat RunPCA function.
Top 50 principal components were used for Uniform manifold approximation and projection and cell clustering.
Cell clustering was performed with the resolution “1.0”.
Differentially expressed genes between clusters or groups were estimated using the Seurat FindAllMarkers function with the option only.pos=TRUE.
Assembly: mm10
Supplementary files format and content: RDS file continaing a Seurat object with raw count data from three samples.
Supplementary files format and content: TSV file containig the result of differential gene expression (DGE) analysis
|
| |
|
| Submission date |
Apr 21, 2023 |
| Last update date |
Feb 19, 2024 |
| Contact name |
Rui Yokomori |
| Organization name |
Cancer Science Institute of Singapore, National University of Singapore
|
| Lab |
Takaomi Sanda Lab
|
| Street address |
14 Medical Drive
|
| City |
Singapore |
| ZIP/Postal code |
117599 |
| Country |
Singapore |
| |
|
| Platform ID |
GPL28457 |
| Series (1) |
| GSE230331 |
Single cell RNA-seq analysis for spleen tissue under steady state, phenohydrazine (PHZ) and bleeding treatment. |
|
| Relations |
| BioSample |
SAMN34299971 |
| SRA |
SRX20054264 |
