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Sample GSM5724716 Query DataSets for GSM5724716
Status Public on Apr 12, 2023
Title PanCK DSP-1001660005232-A-F08
Sample type SRA
 
Source name Normal Lung
Organism Homo sapiens
Characteristics geomx oligo set: Cancer Transcriptome Atlas, (v1.0) GeoMx COVID-19
roi number: 1
ffpe: FFPE tissue
Extracted molecule total RNA
Extraction protocol nanoString GeoMx digital spatial profiling was applied to 3 COVID-19 and 1 normal lung tissues to acquire spatially resolved, quantitative measurements of gene expression in human lung macrophages, granulocytes and epithelium in FFPE tissue sections. Three cases of post-mortem COVID lung tissues and one case of surgically resected normal lung tissue were sectioned, deparaffinized, rehydrated and treated with low pH retrieval solution. nanoString GeoMX Digital Spatial ImmuneOncology and COVID-19 RNA probes were hybridized to sections overnight. Sections were then stained with a cocktail of immunofluorescent antibodies comprised of Alexa fluor 532-labeled anti-CD68 (Clone KP1, 1:100, Novus Biologicals, USA), Alexa fluor 647-labeled Myeloperoxidase (Clone 2C7, 1:500, Novus Biologicals, USA), Alexa fluor 594 labelled anti-PanCytokeratin (C AE-1, AE-3) and Alexa fluor 488 SYTO13 Nuclear stain. Digital scanning of slides was performed on the GeoMX Digital Profiler (nanoString Technologies, Inc.). Regions of Interest (ROI) and cell type with a spatial resolution of approximately 10 mm were selected, exposed to UV light for RNA probe cleavage and oligonucleotide collection.
Samples were sequenced on a NovaSeq6000.
 
Library strategy OTHER
Library source transcriptomic
Library selection other
Instrument model Illumina NovaSeq 6000
 
Description PanCK
RNA (amplified oligo nucleotide probes)
Data processing Counts from barcodes corresponding to RNA probes were normalized with internal positive and negative controls and then normalized to ROI area.
Data were pre-processed in nanoString DSP Software v 2.2.0.123 with Q3 normalization. ROIs were classified according to predominant cell type (epithelium, granulocyte, macrophage) in one of two conditions (COVID-19 positive and normal). The R BioConductor packages edgeR (Robinson et al., 2010) and limma (Ritchie et al., 2015) were used to implement the limma-voom (Law et al., 2014) method for differential expression analysis within and across cell types and condition. Trimmed mean of M-values (TMM) (Robinson and Oshlack, 2010) normalization was applied. The experimental design was modeled upon cell type and condition (~0 + cellType_condition). The voom method was employed to model the mean-variance relationship, after which lmFit was used to fit per-gene linear models and empirical Bayes moderation was applied with the eBayes function. Significance was defined by using an adjusted p-value cut-off of <0.05 after multiple testing correction (Benjamini and Hochberg, 1995) using a moderated t-statistic in limma.
Genome_build: GCA_000001405.15
Supplementary_files_format_and_content: Nanostring GeoMx Q3 normalized data file as csv file, Included relative expression levels of genes
 
Submission date Dec 08, 2021
Last update date Apr 12, 2023
Contact name Judith Varner
E-mail(s) jvarner@ucsd.edu
Phone 8588220086
Organization name University of California, San Diego
Department Moores Cancer Center
Street address 3855 Health Sciences Dr.
City La Jolla
State/province CA
ZIP/Postal code 92093-0819
Country USA
 
Platform ID GPL24676
Series (1)
GSE190494 Nanostring GeoMx digital spatial profliing of myeloid cells from COVID-19 and normal lung
Relations
BioSample SAMN23796529
SRA SRX13355842

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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