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Sample GSM8032509 Query DataSets for GSM8032509
Status Public on Mar 01, 2024
Title CD8andCD4Tcellsfromp-KO1implantedB6mice [p-aKO1-GEX]
Sample type SRA
 
Source name Pancreatic tumor
Organism Mus musculus
Characteristics tissue: Pancreatic tumor
cell line: p-aKO1
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 SAMN39525141
SRA SRX23341570

Supplementary file Size Download File type/resource
GSM8032509_MLT2_02_H11_singleR_filtered_seurat.rds.gz 38.2 Mb (ftp)(http) RDS
SRA Run SelectorHelp
Raw data are available in SRA

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