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Sample GSM5468302 Query DataSets for GSM5468302
Status Public on Apr 12, 2022
Title Allergic patients 3 - 12h - diluent
Sample type SRA
 
Source name PBMC
Organism Homo sapiens
Characteristics treatment: diluent challenged
timepoint: 12h
disease: seasonal allergic rhinitis (SAR)
cell type: PBMC
Treatment protocol PBMCs were challenged with allergen (10 µg/mL birch pollen extract) or diluent, and incubated for different time points in RPMI 1640 supplemented with 10% fetal bovine serum. Samples were obtained at 0 hours (before stimulation), 12 hours, 1 day, 2 days, 3 days, 5 days, and 7 days, for scRNA-seq using the Seq-Well method.
Extracted molecule polyA RNA
Extraction protocol The bam files were extracted following all the steps of James Nemesh, McCarrol’s lab Drop-seq Core Computational Protocol (version 1.0.1) (http://mccarrolllab.com), using bcl2fastq conversion and Picard software.
Libraries were prepared from GRCh38 (April 2017, Ensembl) using STAR software.
 
Library strategy RNA-Seq
Library source transcriptomic
Library selection cDNA
Instrument model Illumina NextSeq 500
 
Data processing Processed of scRNA-seq data into digital gene expression matrices following James Nemesh, McCarrol’s lab Drop-seq Core Computational Protocol (version 1.0.1) (http://mccarrolllab.com) using bcl2fastq conversion and Picard software. The indexed reference for alignment of the reads was generated from GRCh38 (April 2017, Ensembl) using STAR software.
Quality control, where cells with less than 10,000 reads, 400 transcripts, or 200 genes, or more than 20% mitochondrial genes were sorted out.
Noise reduction by k-nearest neighbor smoothing (k = ~0.1% the total number of cells) was applied.
Cell type identification using Reference Component Analysis. The references were produced based on bulk data, from HG_U133A/GNF1H gene atlas and PMID: 31358043.
Genome_build: hg38
Supplementary_files_format_and_content: Matrix table with denoised transcript counts of each gene (rows) within each cell (columns).
 
Submission date Jul 23, 2021
Last update date Apr 12, 2022
Contact name Sandra Lilja
Organization name Linköping University
Department BKV
Street address Sandbäcksgatan 7
City Linköping
ZIP/Postal code 582 25
Country Sweden
 
Platform ID GPL18573
Series (1)
GSE180697 A dynamic single cell-based framework for digital twins to prioritize disease genes and drug targets
Relations
BioSample SAMN20358804
SRA SRX11530031

Supplementary data files not provided
SRA Run SelectorHelp
Raw data are available in SRA
Processed data are available on Series record

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