MED16 negatively regulates erythropoiesis and myelopoiesis through modulation of chromatin accessibility
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 52 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
- Mus musculus (mouse)
- Samples
- 52 samples: 20 conditions, mostly in duplicateGroups 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 GSE248813_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 PRJNA1046045 and SRA study SRP474672. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 40 samples.
How we read this: 20 replicated groups read from 52 sample titles; they account for 40 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.
- GSM7920307 D0CD34shSCR_ATACseq_R1 D0CD34shSCR_ATACseq
- GSM7920308 D0CD34shSCR_ATACseq_R2 D0CD34shSCR_ATACseq
- GSM7920309 D0CD34shMED16_ATACseq_R1 D0CD34shMED16_ATACseq
- GSM7920310 D0CD34shMED16_ATACseq_R2 D0CD34shMED16_ATACseq
- GSM7920311 D4CD34_shSCR_R1 D4CD34_shSCR
- GSM7920312 D4CD34_shSCR_R2 D4CD34_shSCR
- GSM7920313 D4CD34_shMED16_R1 D4CD34_shMED16
- GSM7920314 D4CD34_shMED16_R2 D4CD34_shMED16
- GSM7920315 M16DKd3_ter119_R1 M16DKd3_ter119
- GSM7920316 M16DKd3_ter119_R2 M16DKd3_ter119
- GSM7920317 M16flfld3_ter119_R1 M16flfld3_ter119
- GSM7920318 M16flfld3_ter119_R2 M16flfld3_ter119
- GSM7920319 D0CD34_RUNX1_R1 D0CD34_RUNX1
- GSM7920320 D0CD34_RUNX1_R2 D0CD34_RUNX1
- GSM7920321 D4CD34_RUNX1_R1 D4CD34_RUNX1
- GSM7920322 D4CD34_RUNX1_R2 D4CD34_RUNX1
- GSM7920323 D4CD34SCR_SPT16_R1 D4CD34SCR_SPT16
- GSM7920324 D4CD34SCR_SPT16_R2 D4CD34SCR_SPT16
- GSM7920325 D4CD34SHI_SPT16_R1 D4CD34SHI_SPT16
- GSM7920326 D4CD34SHI_SPT16_R2 D4CD34SHI_SPT16
- GSM7920327 D0CD34_MED16_R1 D0CD34_MED16
- GSM7920328 D0CD34_MED16_R2 D0CD34_MED16
- GSM7920329 D4CD34_MED16_R1 D4CD34_MED16
- GSM7920330 D4CD34_MED16_R2 D4CD34_MED16
- GSM7920331 RUNX1_M16DK
- GSM7920332 RUNX1_M16flfl
- GSM7920333 SPT16_M16DK
- GSM7920334 SPT16_M16flfl
- GSM7920335 MED16_M16DK
- GSM7920336 MED16_M16flfl
- GSM7920405 SCR-1_Day0 SCR-1_Day
- GSM7920406 SCR-2_Day0 SCR-2_Day
- GSM7920407 SH-1_Day0 SH-1_Day
- GSM7920408 SH-2_Day0 SH-2_Day
- GSM7920409 SCR-1_Day4 SCR-1_Day
- GSM7920410 SCR-2_Day4 SCR-2_Day
- GSM7920411 SH-1_Day4 SH-1_Day
- GSM7920412 SH-2_Day4 SH-2_Day
- GSM7920413 VO-1_Day12
- GSM7920414 VO-2_Day12
+ 12 more — browse all 52 samples with per-sample file links →
- GSE255572 Chromatin remodeler CHD7 regulates neurogenic gene expression via controlling chromatin accessibility and modifications of histone marks H3K27me3 and H3K4me3 34 samples shares accessibility, chromatin
- GSE278068 Nanobody-tethered transposition for dual profiling of chromatin accessibility and DNA methylation 201 samples shares accessibility, chromatin
- GSE261788 AMAR-seq: automated multimodal sequencing of DNA methylation, chromatin accessibility, and RNA expression with single-cell resolution 83 samples shares accessibility, chromatin
- GSE291229 Reducing batch effects in single cell chromatin accessibility measurements by pooled transposition with MULTI-ATAC 19 samples shares accessibility, chromatin
- GSE278007 Spatial profiling of chromatin accessibility in formalin-fixed paraffin-embedded tissues 18 samples shares accessibility, chromatin
- GSE68103 Multiplex Single Cell Profiling of Chromatin Accessibility by Combinatorial Cellular Indexing 12 samples shares accessibility, chromatin
- GSE274324 Thymic epithelia amplify noise in chromatin accessibility via p53 repression to impose immune tolerance 8 samples shares accessibility, chromatin
- GSE246859 ChromaFold predicts the 3D contact map from single-cell chromatin accessibility 3 samples shares accessibility, chromatin
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.