2cChIP-seq: an efficient and reliable method for epigenomic profiling of small cell numbers and single cells [2cChIP-seq and 2cMeDIP-seq]
Single-cell RNA-seq · human · 34 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 34 samples
- 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 GSE173281_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA725014 and SRA study SRP316259. Searching any of these in the dataset finder brings you back here.
The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.
+ 34 more — browse all 34 samples with per-sample file links →
- GSE185619 2cChIP-seq: an efficient and reliable method for epigenomic profiling of small cell numbers and single cells 231 samples shares 2cchip-seq, epigenomic, efficient, reliable, numbers, method, small
- GSE150672 Highly Efficient, Massively-Parallel Single-Cell RNA-Seq Reveals Cellular States and Molecular Features of Human Skin Pathology 438 samples shares efficient
- GSE47966 Global epigenomic reconfiguration during mammalian brain development 65 samples shares epigenomic
- GSE267187 DMF-ChIP-seq for Highly Sensitive and Integrated Epigenomic Profiling of Low-input Cells 23 samples shares epigenomic
- GSE80820 HiChIP: Efficient and sensitive analysis of protein-directed genome architecture 18 samples shares efficient
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.