Transcriptional response induced by knockdown of HUWE1 in human HEK293T cells
RNA-seq (gene expression) · human · 20 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
- 20 samples: 8 × HUWE1 vs 4 × non-targeting siRNA vs 4 × HUWE1siRNA vs 4 × NTGroups 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
- Proteome solubility is differentially reshaped by thermal stress and regulators of ubiquitinationThe Journal of biological chemistry · 2025
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 GSE247514_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 PRJNA1039272 and SRA study SRP471337. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 20 samples.
How we read this: 4 replicated groups read from 20 sample titles; they account for 20 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.
- GSM7891087 non-targeting siRNA_1 non-targeting siRNA
- GSM7891088 non-targeting siRNA_2 non-targeting siRNA
- GSM7891089 non-targeting siRNA_3 non-targeting siRNA
- GSM7891090 non-targeting siRNA_4 non-targeting siRNA
- GSM7891091 HUWE1siRNA_1 HUWE1siRNA
- GSM7891092 HUWE1siRNA_2 HUWE1siRNA
- GSM7891093 HUWE1siRNA_3 HUWE1siRNA
- GSM7891094 HUWE1siRNA_4 HUWE1siRNA
- GSM8458455 NT_1 NT
- GSM8458456 NT_2 NT
- GSM8458457 NT_3 NT
- GSM8458458 NT_4 NT
- GSM8458459 HUWE1_5 HUWE1
- GSM8458460 HUWE1_6 HUWE1
- GSM8458461 HUWE1_7 HUWE1
- GSM8458462 HUWE1_8 HUWE1
- GSM8458463 HUWE1_9 HUWE1
- GSM8458464 HUWE1_10 HUWE1
- GSM8458465 HUWE1_11 HUWE1
- GSM8458466 HUWE1_12 HUWE1
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- GSE328981 Quantum Molecular Resonance attenuates an oxidative stress-induced chimeric transcriptome program in human retinal pigment epithelial cells, preserving RNA structural fidelity 108 samples shares induced
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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.