Global impact of unproductive splicing on human gene expression.
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 179 samples
- What it is
- ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
- Organism
- Homo sapiens (human)
- Samples
- 179 samples: 93 × H3K36ME3 Cut&Tag of LCLs, NA vs 86 × naRNA-seq of LCLs, NAGroups 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
- Global impact of unproductive splicing on human gene expressionNature genetics · 2024
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 GSE252006_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA1021544 and SRA study SRP463418. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 179 samples.
How we read this: 2 replicated groups read from 179 sample titles; they account for 179 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.
- GSM7991205 H3K36ME3 Cut&Tag of LCLs, NA18486 H3K36ME3 Cut&Tag of LCL…
- GSM7991206 H3K36ME3 Cut&Tag of LCLs, NA18497 H3K36ME3 Cut&Tag of LCL…
- GSM7991207 H3K36ME3 Cut&Tag of LCLs, NA18498 H3K36ME3 Cut&Tag of LCL…
- GSM7991208 H3K36ME3 Cut&Tag of LCLs, NA18499 H3K36ME3 Cut&Tag of LCL…
- GSM7991209 H3K36ME3 Cut&Tag of LCLs, NA18502 H3K36ME3 Cut&Tag of LCL…
- GSM7991210 H3K36ME3 Cut&Tag of LCLs, NA18504 H3K36ME3 Cut&Tag of LCL…
- GSM7991211 H3K36ME3 Cut&Tag of LCLs, NA18505 H3K36ME3 Cut&Tag of LCL…
- GSM7991212 H3K36ME3 Cut&Tag of LCLs, NA18507 H3K36ME3 Cut&Tag of LCL…
- GSM7991213 H3K36ME3 Cut&Tag of LCLs, NA18508 H3K36ME3 Cut&Tag of LCL…
- GSM7991214 H3K36ME3 Cut&Tag of LCLs, NA18510 H3K36ME3 Cut&Tag of LCL…
- GSM7991215 H3K36ME3 Cut&Tag of LCLs, NA18511 H3K36ME3 Cut&Tag of LCL…
- GSM7991216 H3K36ME3 Cut&Tag of LCLs, NA18516 H3K36ME3 Cut&Tag of LCL…
- GSM7991217 H3K36ME3 Cut&Tag of LCLs, NA18519 H3K36ME3 Cut&Tag of LCL…
- GSM7991218 H3K36ME3 Cut&Tag of LCLs, NA18520 H3K36ME3 Cut&Tag of LCL…
- GSM7991219 H3K36ME3 Cut&Tag of LCLs, NA18522 H3K36ME3 Cut&Tag of LCL…
- GSM7991220 H3K36ME3 Cut&Tag of LCLs, NA18523 H3K36ME3 Cut&Tag of LCL…
- GSM7991221 H3K36ME3 Cut&Tag of LCLs, NA18852 H3K36ME3 Cut&Tag of LCL…
- GSM7991222 H3K36ME3 Cut&Tag of LCLs, NA18853 H3K36ME3 Cut&Tag of LCL…
- GSM7991223 H3K36ME3 Cut&Tag of LCLs, NA18855 H3K36ME3 Cut&Tag of LCL…
- GSM7991224 H3K36ME3 Cut&Tag of LCLs, NA18858 H3K36ME3 Cut&Tag of LCL…
- GSM7991225 H3K36ME3 Cut&Tag of LCLs, NA18861 H3K36ME3 Cut&Tag of LCL…
- GSM7991226 H3K36ME3 Cut&Tag of LCLs, NA18862 H3K36ME3 Cut&Tag of LCL…
- GSM7991227 H3K36ME3 Cut&Tag of LCLs, NA18864 H3K36ME3 Cut&Tag of LCL…
- GSM7991228 H3K36ME3 Cut&Tag of LCLs, NA18867 H3K36ME3 Cut&Tag of LCL…
- GSM7991229 H3K36ME3 Cut&Tag of LCLs, NA18868 H3K36ME3 Cut&Tag of LCL…
- GSM7991230 H3K36ME3 Cut&Tag of LCLs, NA18870 H3K36ME3 Cut&Tag of LCL…
- GSM7991231 H3K36ME3 Cut&Tag of LCLs, NA18876 H3K36ME3 Cut&Tag of LCL…
- GSM7991232 H3K36ME3 Cut&Tag of LCLs, NA18877 H3K36ME3 Cut&Tag of LCL…
- GSM7991233 H3K36ME3 Cut&Tag of LCLs, NA18879 H3K36ME3 Cut&Tag of LCL…
- GSM7991234 H3K36ME3 Cut&Tag of LCLs, NA18881 H3K36ME3 Cut&Tag of LCL…
- GSM7991235 H3K36ME3 Cut&Tag of LCLs, NA18907 H3K36ME3 Cut&Tag of LCL…
- GSM7991236 H3K36ME3 Cut&Tag of LCLs, NA18909 H3K36ME3 Cut&Tag of LCL…
- GSM7991237 H3K36ME3 Cut&Tag of LCLs, NA18910 H3K36ME3 Cut&Tag of LCL…
- GSM7991238 H3K36ME3 Cut&Tag of LCLs, NA18912 H3K36ME3 Cut&Tag of LCL…
- GSM7991239 H3K36ME3 Cut&Tag of LCLs, NA18913 H3K36ME3 Cut&Tag of LCL…
- GSM7991240 H3K36ME3 Cut&Tag of LCLs, NA18915 H3K36ME3 Cut&Tag of LCL…
- GSM7991241 H3K36ME3 Cut&Tag of LCLs, NA18917 H3K36ME3 Cut&Tag of LCL…
- GSM7991242 H3K36ME3 Cut&Tag of LCLs, NA18923 H3K36ME3 Cut&Tag of LCL…
- GSM7991243 H3K36ME3 Cut&Tag of LCLs, NA18924 H3K36ME3 Cut&Tag of LCL…
- GSM7991244 H3K36ME3 Cut&Tag of LCLs, NA18934 H3K36ME3 Cut&Tag of LCL…
+ 139 more — browse all 179 samples with per-sample file links →
- GSE325047 Pervasive Enhanced Transcription in Inflammatory Breast Cancer Tumors and PBMCs Impacts RNA Splicing and Intronic RNAs in Plasma 80 samples shares splicing, impact
- GSE279274 Alternative splicing is an FXRα loss-of-function mechanism and impacts energy metabolism in hepatocarcinoma cells. 16 samples shares splicing, impact
- GSE47729 Global peripheral blood gene expression study 350 samples shares global
- GSE334189 RNA-seq analysis of global gene expression changes in human FSHD immortalized myotubes following treatment with the BAZ1A inhibitor C06 18 samples shares global
- GSE130955 Global skin gene expression profile of early diffuse cutaneous systemic sclerosis shows a prominent innate and adaptive immunity profile 91 samples shares global
- GSE266132 Impact of the Multiple Sclerosis associated genetic variant CD226 Gly307Ser on human CD8 T cell functions 80 samples shares impact
- GSE287072 Alternative splicing and differential gene expression during changes in endometrial receptivity in patients with recurrent implantation failure 73 samples shares splicing
- GSE266455 hiv-seq reveals global host gene expression differences between hiv-transcribing cells from viremic and suppressed people with hiv 48 samples shares global
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.