Unraveling Novel Drug candidate for ALS through an Integrative Network Analysis of approved Drug-Gene Expression Signatures in Human Pluripotent Stem Cell-Based Model
RNA-seq (gene expression) · human · 151 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
- 151 samples: 51 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.
Read the full summary ↓
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 GSE261648_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 PRJNA1088159 and SRA study SRP495345. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 151 samples.
How we read this: 51 replicated groups read from 151 sample titles; they account for 151 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.
- GSM8147884 Amoxa, Replicate 1 Amoxa,
- GSM8147885 Amoxa, Replicate 2 Amoxa,
- GSM8147886 Amoxa, Replicate 3 Amoxa,
- GSM8147888 Argat, Replicate 1 Argat,
- GSM8147889 Argat, Replicate 2 Argat,
- GSM8147890 Argat, Replicate 3 Argat,
- GSM8147892 ChloDipho, Replicate 1 ChloDipho,
- GSM8147893 ChloDipho, Replicate 2 ChloDipho,
- GSM8147894 ChloDipho, Replicate 3 ChloDipho,
- GSM8147896 CyprHydro, Replicate 1 CyprHydro,
- GSM8147897 CyprHydro, Replicate 2 CyprHydro,
- GSM8147899 CyprHydro, Replicate 3 CyprHydro,
- GSM8147900 Dexme, Replicate 1 Dexme,
- GSM8147901 Dexme, Replicate 2 Dexme,
- GSM8147903 Dexme, Replicate 3 Dexme,
- GSM8147904 DivaSodium, Replicate 1 DivaSodium,
- GSM8147905 DivaSodium, Replicate 2 DivaSodium,
- GSM8147907 DivaSodium, Replicate 3 DivaSodium,
- GSM8147908 DMSO, Replicate 1 DMSO,
- GSM8147910 DMSO, Replicate 2 DMSO,
- GSM8147911 DMSO, Replicate 3 DMSO,
- GSM8147912 DMSO, Replicate 4 DMSO,
- GSM8147913 DoxeHydro, Replicate 1 DoxeHydro,
- GSM8147914 DoxeHydro, Replicate 3 DoxeHydro,
- GSM8147915 EsomMagne, Replicate 1 EsomMagne,
- GSM8147916 EsomMagne, Replicate 2 EsomMagne,
- GSM8147917 EsomMagne, Replicate 3 EsomMagne,
- GSM8147918 Fenof, Replicate 1 Fenof,
- GSM8147919 Fenof, Replicate 2 Fenof,
- GSM8147920 Fenof, Replicate 3 Fenof,
- GSM8147921 Fluco, Replicate 1 Fluco,
- GSM8147922 Fluco, Replicate 2 Fluco,
- GSM8147923 Fluco, Replicate 3 Fluco,
- GSM8147924 FludAceta, Replicate 1 FludAceta,
- GSM8147925 FludAceta, Replicate 2 FludAceta,
- GSM8147926 FluoHydro, Replicate 1 FluoHydro,
- GSM8147927 FluoHydro, Replicate 2 FluoHydro,
- GSM8147928 FluoHydro, Replicate 3 FluoHydro,
- GSM8147929 Furos, Replicate 1 Furos,
- GSM8147930 Furos, Replicate 2 Furos,
+ 111 more — browse all 151 samples with per-sample file links →
- GSE315442 Transcriptomic profiling reveals distinct molecular signatures among lesion types in hidradenitis suppurativa 48 samples shares als, signatures
- GSE270387 Single cell profiling of peripheral blood mononuclear cells in diverse men with prostate cancer reveals lethal disease-associated immune signatures 165 samples shares als, signatures
- GSE233321 Single-cell map of the healthy human immune system across the lifespan reveals unique infant immune signatures 118 samples shares als, signatures
- GSE330130 A multi-omics characterization of the human lumbar spinal cord and motor cortex reveals non-overlapping molecular signatures in ALS [snRNA-Seq; snATAC-Seq] 87 samples shares als, signatures
- GSE305971 Integrative single-cell analysis reveals malignant archetypes and proliferative hierarchies in multiple myeloma 2105 samples shares als
- GSE314342 Genome-scale perturb-seq in primary human CD4+ T cells reveals genes regulating T cell programs and human immune traits. 577 samples shares als
- GSE263733 Single-cell transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implications 218 samples shares als
- GSE328048 Single-cell transcriptome reveals keratinocyte subclusters that contribute to altered differentiation and inflammatory responses in atopic dermatitis 116 samples shares als
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.