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Effect of FOSL1 and HDAC2 knockdown on gene expression in cancer cell lines

GSE230729 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/04/27 Platform GPL20795
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × H1299 cells, shHDAC2, biol vs 3 × H1299 cells, shControl, biol vs 3 × PANC-1 cells, shFOSL1, biol vs 3 × PANC-1 cells, shControl, biolGroups 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.
Paper
Single cell atlas reveals multilayered metabolic heterogeneity across tumour typesEBioMedicine · 2024
Summary (written by the submitters)
We identifled FOSL1 and HDAC2 as master regulators of cancer cell metabolism. To validate their function, we knockdown FOSL1 in pancreatic adenocarcinoma cell line PANC-1 and HDAC2 in lung adenocarcinoma cell line H1299, respectively. Then RNA-seq was performed to investigate the alterations of metabolic genes.
Published in
Single cell atlas reveals multilayered metabolic heterogeneity across tumour types
Zhou Z, Dong D, Yuan Y et al. · EBioMedicine 2024 · PMID 39393173 · doi:10.1016/j.ebiom.2024.105389
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 GSE230729_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 PRJNA962475 and SRA study SRP434823. Searching any of these in the dataset finder brings you back here.

Study design
3 × H1299 cells, shHDAC2, biol vs 3 × H1299 cells, shControl, biol vs 3 × PANC-1 cells, shFOSL1, biol vs 3 × PANC-1 cells, shControl, biol

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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