Normal human bronchial epithelial cell Next Gen sequencing (RNA-seq) for differential gene expression of untreated versus IL4 or IL4+ALOX15 siRNA treated cells
RNA-seq (gene expression) · human · 18 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 18 samples: 18 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE179420_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA743661 and SRA study SRP326869. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 18 sample titles: 18 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM5417445 Sample 1_NHBE, Control untreated
- GSM5417446 Sample 2_NHBE, Control untreated
- GSM5417447 Sample 3_NHBE, Control untreated
- GSM5417448 Sample 4_NHBE, 10 ng/ml IL4
- GSM5417449 Sample 5_NHBE, 10 ng/ml IL4
- GSM5417450 Sample 6_NHBE, 10 ng/ml IL4
- GSM5417451 Sample 7_NHBE, 10 ng/ml IL4 + Compound A
- GSM5417452 Sample 8_NHBE, 10 ng/ml IL4 + Compound A
- GSM5417453 Sample 9_NHBE, 10 ng/ml IL4 + Compound A
- GSM5417454 Sample 10_NHBE, 10 ng/ml IL4 + Compound B
- GSM5417455 Sample 11_NHBE, 10 ng/ml IL4 + Compound B
- GSM5417456 Sample 12_NHBE, 10 ng/ml IL4 + Compound B
- GSM5417457 Sample 13_NHBE, 10 ng/ml IL4 + Control Smartpool siRNA
- GSM5417458 Sample 14_NHBE, 10 ng/ml IL4 + Control Smartpool siRNA
- GSM5417459 Sample 15_NHBE, 10 ng/ml IL4 + Control Smartpool siRNA
- GSM5417460 Sample 16_NHBE, 10 ng/ml IL4 + ALOX15 Smartpool siRNA
- GSM5417461 Sample 17_NHBE, 10 ng/ml IL4 + ALOX15 Smartpool siRNA
- GSM5417462 Sample 18_NHBE, 10 ng/ml IL4 + ALOX15 Smartpool siRNA
- GSE292059 Inflammatory Epithelial and Macrophage Pathways Underlie Residual Asthma Exacerbations in Urban Children Treated with Mepolizumab 965 samples shares epithelial, treated
- GSE275647 Role of Cancer-Associated Fibroblasts in Prognostic Stratification of Advanced-Stage Gastric Cancer through Interacting with Endothelial and Malignant Epithelial Cells [AGC RNA-seq] 216 samples shares epithelial, rna-seq
- GSE314526 Differential Cellular Mechanisms Underlie Language and Executive Decline in Amyotrophic Lateral Sclerosis [RNA-seq] 72 samples shares differential, rna-seq
- GSE282444 Epigenetic Memory of Intestinal Epithelial Cells in Inflammatory Bowel Disease [RNA-seq] 56 samples shares epithelial, rna-seq
- GSE161245 Comparison of bronchial epithelial cells obtained by bronchoscopy from mild asthma patients, moderate asthma patients, severe asthma patients and healthy controls 55 samples shares epithelial, bronchial
- GSE276503 Myeloid-derived IL1B drives epithelial and stromal cell remodeling during chronic rhinosinusitis and nasal polyps [scRNA-seq] 33 samples shares epithelial, rna-seq
- GSE304598 Bulk RNA-seq time-course of human iPSc differentiation to thymic epithelial progenitors 33 samples shares epithelial, rna-seq
- GSE289073 Single-cell mapping of human endometrium and decidua reveals epithelial and stromal contributions to fertility [bulk RNA-seq] 26 samples shares epithelial, rna-seq
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.