 |
 |
GEO help: Mouse over screen elements for information. |
|
| Status |
Public on Apr 12, 2022 |
| Title |
Allergic patients 2 - day2 - diluent |
| Sample type |
SRA |
| |
|
| Source name |
PBMC
|
| Organism |
Homo sapiens |
| Characteristics |
treatment: diluent challenged
timepoint: day2
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 |
SAMN20358813 |
| SRA |
SRX11530022 |
| Supplementary data files not provided |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
|
|
|
|
 |
