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RNA sequencing of bronchial epithelial cells cultured in air-liquid interface for 7 days treated or not with an antibody targeting the sonic hedgehog ligand (AB5E1)

GSE262404 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2024/08/20 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 10 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
10 samples: 5 × CTL ALI7, patient vs 5 × AB5E1 ALI7, patientGroups 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.
Summary (written by the submitters)
The hedgehog pathway is crucial during airway epithelial cell differentiation. To assess the transcriptomic print of airway epithelial cells in absence of hedgehog pathway activation, we performed a comparative transcriptomic analysis on air-liquid interface cell cultures. Bronchial epithelial cells from 5 non-COPD subjects (ex- and current smokers) were isolated from bronchial brushes and cultured in air-liquid interface.
Read the full summary ↓
The total RNA were extracted after 7 days of culture in air-liquid conditions in presence of an antibody targeting the sonic hedgehog ligand (AB5E1) or not (CTL). The libraries were prepared with NEBNext Ultra II directeional RNA Library Prep Kit and sequenced on Illumina.
This dataset
Download · which file do I need?

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.

1 · Just have a look

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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE262404_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

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 PRJNA1091651 and SRA study SRP497781. Searching any of these in the dataset finder brings you back here.

Study design
5 × CTL ALI7, patient vs 5 × AB5E1 ALI7, patient

Supports a between-group comparison across 10 samples.

How we read this: 2 replicated groups read from 10 sample titles; they account for 10 of them. 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.

Samples in this study
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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.