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Single-nucleus chromatin accessibility and transcriptomic characterization of Alzheimer’s Disease

GSE174367 Homo sapiens (human) Single-nucleus RNA-seq 230 samples Submitted 2021/05/12 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 230 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism
Homo sapiens (human)
Samples
230 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.
Summary (written by the submitters)
The gene-regulatory landscape of the brain is highly dynamic in health and disease, coordinating a menagerie of biological processes across¬ distinct cell-types. Here, we present a multi-omic single-nucleus study of 191,890 nuclei in late-stage Alzheimer’s Disease (AD), accessible through our intuitive web portal, profiling chromatin accessibility and gene expression in the same biological samples and uncovering vast cellular heterogeneity.
Read the full summary ↓
We identified cell-type specific, disease-associated candidate cis-regulatory elements and their candidate target genes, including an oligodendrocyte-associated regulatory module containing links to APOE and CLU. We describe cis-regulatory relationships in specific cell-types at AD risk loci defined by genome wide association studies (GWAS), demonstrating the utility of this multi-omic single-nucleus approach. Trajectory analysis of glial populations identified disease-relevant transcription factors, like SREBF1 and their regulatory targets. Further, we introduce scWGCNA, a co-expression network analysis strategy robust to the sparsity of single-cell data, to perform a systems-level meta-analysis of AD transcriptomics.
This dataset
Open GSE174367 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE174367_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA729525 and SRA study SRP319543. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 34239132) ↗
Samples in this study

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+ 230 more — browse all 230 samples with per-sample file links →

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