Epigenetic Analysis of SLE Disease Activity in Resting Naive (rN) and Transitional (T1T2) B cells
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 62 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
- 62 samples: 62 samples, each with a distinct title — no replicated groupsGroups 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 GSE263716_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 PRJNA1098772 and SRA study SRP500837. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 62 sample titles: 62 distinct titles with little repetition. 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.
- GSM8197150 SLE.1929.1537.rN ATAC
- GSM8197151 SLE.1929.1537.T1-2 ATAC
- GSM8197152 SLE.1551.1597.rN ATAC
- GSM8197153 SLE.1731.1738.rN ATAC
- GSM8197154 SLE.2711.871.rN ATAC
- GSM8197155 SLE.3202.2491.rN ATAC
- GSM8197156 HCD.918.1215.rN ATAC
- GSM8197157 HCD.918.1215.T1-2 ATAC
- GSM8197158 HCD.646.1234.rN ATAC
- GSM8197159 HCD.646.1234.T1-2 ATAC
- GSM8197160 HCD.796.1235.rN ATAC
- GSM8197161 HCD.1171.1296.rN ATAC
- GSM8197162 HCD.1171.1296.T1-2 ATAC
- GSM8197163 HCD.878.1606.rN ATAC
- GSM8197164 SLE.2913.559.rN ATAC
- GSM8197165 SLE.2913.559.T1-2 ATAC
- GSM8197166 SLE.2911.2209.rN ATAC
- GSM8197167 SLE.2911.2209.T1-2 ATAC
- GSM8197168 SLE.2932.3240.rN ATAC
- GSM8197169 SLE.3136.3378.rN ATAC
- GSM8197170 SLE.2891.420.rN ATAC
- GSM8197171 SLE.2891.420.T1-2 ATAC
- GSM8197172 SLE.2880.3039.rN ATAC
- GSM8197173 SLE.2900.3328.rN ATAC
- GSM8197174 SLE.2900.3328.T1-2 ATAC
- GSM8197175 SLE.2898.3314.rN ATAC
- GSM8197176 HCD.875.1610.rN ATAC
- GSM8197177 HCD.875.1610.T1-2 ATAC
- GSM8197178 HCD_691_1086_T1T2 ATAC
- GSM8197179 HCD_623_1256_T1T2 ATAC
- GSM8197180 HCD_1176_1842_rN ATAC
- GSM8197181 HCD_1176_1842_T1T2 ATAC
- GSM8197182 HCD_722_761_T1T2 ATAC
- GSM8197183 SLE_2886_3054_rN ATAC
- GSM8197184 SLE_2886_3054_T1T2 ATAC
- GSM8197185 SLE_1724_1324_rN ATAC
- GSM8197186 SLE_1724_1324_T1T2 ATAC
- GSM8197187 SLE_1638_1655_rN ATAC
- GSM8197188 HCD_862_456_rN ATAC
- GSM8197189 SLE_3117_3239_T1T2 ATAC
+ 22 more — browse all 62 samples with per-sample file links →
- GSE262846 Transcriptomic Analysis of SLE Disease Activity in Resting Naive (rN) and Transitional (T1T2) B cells 88 samples shares t1t2, sle, transitional, activity, resting, naive
- GSE263717 Epigenomic profiles of SLE resting and transitional B cells 150 samples shares sle, transitional, resting
- GSE296831 Epigenetic Context Defines the Transcriptional Activity of Canonical and Noncanonical NF-kappaB Signaling in Pancreatic Cancer [ChIP-Seq] 48 samples shares epigenetic, activity
- GSE319130 Multi-omic analysis reveals molecular subtypes with distinct immunological phenotypes in SLE [RNA-Seq] 804 samples shares sle
- GSE275610 scRNA-seq and snATAC-seq reveal differentiation trajectories of several pancreatic islet induction protocols 341 samples shares sle
- GSE283703 Transcriptome analysis of adult patients with severe Obstructive Sleep Apnea before and after CPAP treatment. 71 samples shares sle
- GSE324084 Transcriptomic analyses of human islets 58 samples shares sle
- GSE263018 Sleeve Gastrectomy Reveals the Plasticity of the Human Gastric Epithelium 31 samples shares sle
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.