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Status |
Public on Apr 12, 2023 |
Title |
CD68 DSP-1001660005232-A-E01 |
Sample type |
SRA |
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Source name |
C13 COVID LUNG
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Organism |
Homo sapiens |
Characteristics |
geomx oligo set: Cancer Transcriptome Atlas, (v1.0) GeoMx COVID-19 roi number: 3 ffpe: FFPE tissue
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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.
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Library strategy |
OTHER |
Library source |
transcriptomic |
Library selection |
other |
Instrument model |
Illumina NovaSeq 6000 |
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Description |
CD68 RNA (amplified oligo nucleotide probes)
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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
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Submission date |
Dec 08, 2021 |
Last update date |
Apr 12, 2023 |
Contact name |
Judith Varner |
E-mail(s) |
jvarner@ucsd.edu
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Phone |
8588220086
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Organization name |
University of California, San Diego
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Department |
Moores Cancer Center
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Street address |
3855 Health Sciences Dr.
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City |
La Jolla |
State/province |
CA |
ZIP/Postal code |
92093-0819 |
Country |
USA |
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Platform ID |
GPL24676 |
Series (1) |
GSE190494 |
Nanostring GeoMx digital spatial profliing of myeloid cells from COVID-19 and normal lung |
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Relations |
BioSample |
SAMN23796600 |
SRA |
SRX13355791 |
Supplementary data files not provided |
SRA Run Selector |
Raw data are available in SRA |
Processed data are available on Series record |
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