|
| Status |
Public on Mar 01, 2024 |
| Title |
CD8andCD4Tcellsfromp-KO2implantedB6mice [p-aKO2-GEX] |
| Sample type |
SRA |
| |
|
| Source name |
Pancreatic tumor
|
| Organism |
Mus musculus |
| Characteristics |
tissue: Pancreatic tumor
cell line: p-aKO2
cell type: pancreatic cells
genotype: KrasG12D; Trp53R172H; Pdx1-Cre; Pik3ca-/-; Pccb-/-
treatment: N/A
|
| Growth protocol |
Tumor cells were implanted to the pancreas of mice for 12 days
|
| Extracted molecule |
total RNA |
| Extraction protocol |
After 12 days post implantation, pancreaetic tumors were harvested and tumor infiltrating CD4 and CD8 were selected by beads.
Libraries for both 5' gene expression and T cell receptors were prepared by 10x genomics' protocol. Briefly,
scRNA seq of gene expression and correponding TCR sequencing
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic single cell |
| Library selection |
cDNA |
| Instrument model |
Illumina NovaSeq 6000 |
| |
|
| Description |
5'GEXby10xgenomics
|
| Data processing |
The Cell Ranger v7.0.0 pipeline was used to demultiplex and align sequencing data to the “ENSEMBL GRCm39” mouse transcriptome to generate gene expression matrices. The Cell Ranger VDJ pipeline was used to assemble sequences and identify paired clonotypes on the V(D)J libraries. The gene expression matrices were further analyzed by the Seurat R package. Three quality control criteria were employed to filter the matrices to exclude unwanted sources of variations: number of detected transcripts, genes, and percent of reads mapping to mitochondrial genes. Cells with UMIs over the interquartile range of 95% (potential doublets) and under 1000 (potential fragments) or a mitochondrial proportion higher than 20% (potential apoptotic) were removed. Moreover, we used the Doublet Finder R algorithm to further eliminate doublet contamination. After the quality control, we annotated cellular identity using the R package SingleR, which assigns each cell to a reference type that has the most similar expression profile with. In further analysis, sctransform package in Seurat was used to normalize UMI count data. The principal component analysis (PCA) of high-dimensional data was performed to identify highly variable genes in each sample, and the top principal components were selected for unsupervised clustering of cells with a graph-based clustering and visualized with Uniform Manifold Approximation and Projection (UMAP).
Assembly: ENSEMBL GRCm39
Supplementary files format and content: The GEX files are in the format of Serut object; the TCR files are in excel files with different cdr3 sequences
|
| |
|
| Submission date |
Jan 23, 2024 |
| Last update date |
Mar 01, 2024 |
| Contact name |
Richard Lin |
| E-mail(s) |
Richard.Lin@stonybrook.edu
|
| Organization name |
Stony Brook University
|
| Street address |
1 Circle Road
|
| City |
Stony Brook |
| ZIP/Postal code |
11790 |
| Country |
USA |
| |
|
| Platform ID |
GPL24247 |
| Series (1) |
| GSE254041 |
Depletion of PCCB and/or PIK3CA from pancreatic tumor cells KPC influences T cells infiltrating to TME |
|
| Relations |
| BioSample |
SAMN39525142 |
| SRA |
SRX23341571 |
