Gene expression profile Predictor on chemical Structures (GPS): Deep Learning-based platform to screen and design novel therapeutics
RNA-seq (gene expression) · human · 27 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
- 27 samples: 5 conditions, mostly in triplicateGroups 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 GSE291867_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 PRJNA1235680 and SRA study SRP570137. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 15 samples.
How we read this: 5 replicated groups read from 27 sample titles; they account for 15 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.
- GSM8830588 IPF295_Drug
- GSM8830589 IPF295_DMSO
- GSM8830590 IPF318_Drug
- GSM8830591 IPF318_DMSO
- GSM8830592 IPF322_Drug
- GSM8830593 IPF322_DMSO
- GSM8830594 IPF294_Drug
- GSM8830595 IPF294_DMSO
- GSM8830596 IPF296_Drug
- GSM8830597 IPF296_DMSO
- GSM8830598 IPF297_Drug
- GSM8830599 IPF297_DMSO
- GSM8843049 HCC_CDX_S302_replicate1 HCC_CDX_S302
- GSM8843050 HCC_CDX_S302_replicate2 HCC_CDX_S302
- GSM8843051 HCC_CDX_S302_replicate3 HCC_CDX_S302
- GSM8843052 HCC_CDX_DMSO_replicate1 HCC_CDX_DMSO
- GSM8843053 HCC_CDX_DMSO_replicate2 HCC_CDX_DMSO
- GSM8843054 HCC_CDX_DMSO_replicate3 HCC_CDX_DMSO
- GSM9378793 Huh7 cells/ PB56874852 treatment/10uM/Rep1 Huh7 cells/ PB56874852 …
- GSM9378794 Huh7 cells/ PB56874852 treatment/10uM/Rep2 Huh7 cells/ PB56874852 …
- GSM9378795 Huh7 cells/ PB56874852 treatment/10uM/Rep3 Huh7 cells/ PB56874852 …
- GSM9378796 Huh7 cells/ PB56874852 treatment/4uM/Rep1 Huh7 cells/ PB56874852 …
- GSM9378797 Huh7 cells/ PB56874852 treatment/4uM/Rep2 Huh7 cells/ PB56874852 …
- GSM9378798 Huh7 cells/ PB56874852 treatment/4uM/Rep3 Huh7 cells/ PB56874852 …
- GSM9378799 Huh7 cells/ DMSO treatment/control/Rep1 Huh7 cells/ DMSO treatm…
- GSM9378800 Huh7 cells/ DMSO treatment/control/Rep2 Huh7 cells/ DMSO treatm…
- GSM9378801 Huh7 cells/ DMSO treatment/control/Rep3 Huh7 cells/ DMSO treatm…
- GSE307568 Patient-derived organoid – immune cell co-culture platform for therapeutics discovery in high-grade endometrial cancer 189 samples shares therapeutics, platform
- GSE279769 Chemically modified CRISPR-Cas9 enables targeting of individual G-quadruplex and i-motif structures, revealing ligand-dependent transcriptional perturbation 21 samples shares structures, chemical
- GSE196524 Integrated transcriptomic and in silico drug screening identifies potential stroma-targeting therapeutics in pancreatic cancer 48 samples shares therapeutics, screen
- GSE250075 GPS2 and HDAC3 RNA-Seq in GPS2-KO MCF-7 [RNA-Seq] 6 samples shares gps
- GSE243251 the effect of UMI-77 on HGPS-MSCs gene expression during cellular senescence 6 samples shares gps
- GSE269484 Differential gene expression in immortalised fibroblasts derived two independent Nestor Guillermo Progeria Syndrome (NGPS) patients, compared to immortalised fibroblasts of an healthy individual 3 samples shares gps
- GSE250076 GPS2 and HDAC3 ChIP-Seq and RNA-Seq in GPS2-KO MCF-7 14 samples shares gps
- GSE69391 Expression data from young and old healthy humans, as well as HGPS patients 12 samples shares gps
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.