Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion
Understanding complex tissues requires single-cell deconstruction of gene regulation with precision and scale. Here we present a massively parallel droplet-based platform for mapping transposase-accessible chromatin in tens of thousands of single cells per sample (scATAC-seq). We obtain and analyze chromatin profiles of over 200,000 single cells in two primary human systems. In blood, scATAC-seq allows marker-free identification of cell type-specific cis- and trans-regulatory elements, mapping o...
Provenance — who produced it, who reused it
Linked to 23 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
- ArchR is a scalable software package for integrative single-cell... 2021 · 1,452 cites
- Comprehensive analysis of single cell ATAC-seq data with SnapATA... 2021 · 484 cites
- MultiVI: deep generative model for the integration of multimodal... 2023 · 310 cites
- Integrative analyses of single-cell transcriptome and regulome u... 2020 · 215 cites
- EpiScanpy: integrated single-cell epigenomic analysis 2021 · 144 cites
- A framework for clinical cancer subtyping from nucleosome profil... 2022 · 127 cites
- PeakVI: A deep generative model for single-cell chromatin access... 2022 · 107 cites
- Integrative single-cell analysis of allele-specific copy number... 2021 · 77 cites
14 further papers cite this accession but reuse could not be confirmed.
Deep data QC
insufficient data to scoreStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
The insufficient grade is a transparent weighted average. Each metric below scored from 0–100% against the published ATAC-seq thresholds, weighted by its importance; nothing is hidden or subjective.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0