d0632693bee08bf61b7990e0c6a1de8c050e337f mspeir Sat Aug 1 20:53:09 2026 -0700 singleCellSignalsPeaks: color by cell class, harmonize labels and facets (hg38) Overhaul of the hg38 track and the shared build scripts it and the mm10 track are generated from: - Color every subtrack by broad cell class from one colorblind-conscious palette (shared with the mm10 track, so a class is the same color on both assemblies); add a color legend to the description page. - Add a "Cell class" facet; the fine cell type becomes a searchable table column. Group subtracks by class via priority; every subtrack is off by default. - Paper-curated cell-type names, redundant-synonym merges, QC-cluster drop, and per-collection tissue/life-stage/condition (including the SEA-AD region and ADNC neuropathology level, from Gabitto 2024 and Hawrylycz 2024). - Rebuild the longLabels from the harmonized cell type + facets, so the cryptic source short labels decode. - Reclassify 10 mislabeled interaction bigBeds out of the signal/peaks composite, retype a narrowPeak-format bigBed, and drop deprecated *.old data (936 -> 925 subtracks). - Archive the curation with the scripts: build_celltype_crosswalks.py and celltype-crosswalks/ (per-collection crosswalks, palette, class map, and the paper-decode source tables). refs #37914 Co-Authored-By: Claude Opus 4.8 (1M context) diff --git src/hg/makeDb/trackDb/human/hg38/singleCellSignalsPeaks.html src/hg/makeDb/trackDb/human/hg38/singleCellSignalsPeaks.html index da1cc38351c..50f2215eb6f 100644 --- src/hg/makeDb/trackDb/human/hg38/singleCellSignalsPeaks.html +++ src/hg/makeDb/trackDb/human/hg38/singleCellSignalsPeaks.html @@ -1,266 +1,312 @@

Description

This track collects the cell-type chromatin accessibility tracks from the single-cell ATAC-seq datasets in the UCSC Cell Browser. For each dataset it shows the read-coverage signal (bigWig) and, where the study reported them, the accessible-region peak calls (bigBed and narrowPeak), split out by cell type. The datasets cover several human tissues, including brain, heart, and retina.

The subtracks come from these datasets:

Display Conventions and Configuration

This is a faceted collection, so the subtracks are chosen with filter menus rather than a long checkbox list. Use the facets on the track configuration page to narrow the subtracks by dataset, tissue, life stage, condition, data type, assay, and cell type, then turn on the ones you want. Signal subtracks draw as coverage graphs and peak subtracks draw as boxes. Each subtrack links back to its source dataset in the Cell Browser.

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+Subtracks are colored by broad cell-type class, so the same class is shown in the same color across datasets and matches the coloring of the corresponding mouse track. The classes are: +

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 Excitatory neuron — glutamatergic neurons of the cortical layers, hippocampal CA fields and dentate gyrus, and claustrum
 Inhibitory neuron — GABAergic neurons and interneurons (Pvalb, Sst, Lamp5, and CGE- and MGE-derived types)
 Medium spiny neuron — striatal D1 and D2 projection neurons of the direct and indirect pathways
 Other neuron — remaining neuronal types, such as Cajal-Retzius cells
 Neural progenitor — neuroblasts, radial glia, and nephron progenitors
 Astrocyte — astrocytes, including Bergmann glia and fibrous and protoplasmic subtypes
 Oligodendrocyte — oligodendrocytes across the newly-formed, myelin-forming, and mature stages
 Oligodendrocyte precursor — oligodendrocyte precursor cells (OPCs) and committed precursors
 Microglia — microglia and perivascular macrophages
 Endothelial — endothelial cells of arteries, capillaries, veins, and endocardium
 Mural — pericytes, smooth muscle, and vascular leptomeningeal cells
 Immune — lymphoid (B, T) and myeloid (macrophage, dendritic, basophil) immune cells
 Erythroid — erythroid cells and erythroblasts
 Hematopoietic stem/progenitor — hematopoietic stem and progenitor cells
 Cardiomyocyte — heart muscle cells
 Muscle — skeletal muscle myofibers, satellite cells, and junctional myonuclei
 Epithelial — epithelial cells of many tissues, such as airway, gut, kidney tubule, and secretory epithelia
 Stromal — fibroblasts, mesenchymal, and other stromal cells
 Other — other or mixed cell types, such as olfactory ensheathing cells and melanocytes
 Unknown — cell type not resolved from the source data
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Methods

Each dataset was produced and processed by a different group, so the assays and analysis pipelines vary. The signal and peak files here are the same ones served by the individual Cell Browser datasets, copied into the browser without change. The table summarizes each dataset; see the linked publication for full detail.

DatasetAssayProcessing summary
Human Enhancer Atlas single-cell ATAC-seq (adult and fetal tissues) Accessibility profiled across 30 adult and 15 fetal tissues, integrated to call about 1.2 million candidate cis-regulatory elements across 222 cell types.
Cortex ATAC 10x single-cell ATAC-seq Developing human cortex and organoid nuclei clustered by accessibility; gene-activity signal derived from accessibility near genes.
Human and Mouse Retina Cell Atlas single-nucleus ATAC-seq Retinal nuclei clustered into cell types, with per-cell-type coverage and peak calls.
Risk Loci in Alzheimer's and Parkinson's 10x single-cell ATAC-seq 70,631 nuclei from six adult brain regions clustered by iterative LSI; peaks called per cluster with MACS2 (501 bp summits, blacklist-filtered), giving 359,022 cell type-specific elements.
Multiomic Human Heart single-nucleus ATAC-seq (with snRNA-seq) 106 snATAC datasets processed with SnapATAC2, batch-corrected by donor and study, integrated with expression from 299 donors.
Human Cardiogenesis single-cell ATAC-seq Human fetal hearts from three early stages profiled to map dynamic regulatory elements across cardiac differentiation trajectories.
Oligodendrocytes in Mouse EAE Model of MS single-cell ATAC-seq Accessibility of the oligodendrocyte lineage; the human tracks show accessibility in oligodendroglia from adult human brain.
BrainVar single-nucleus ATAC-seq Prenatal dorsolateral prefrontal cortex nuclei summarized as gene-activity coverage per major cell class.
SEA-AD Brain ATAC single-nucleus ATAC-seq Pseudobulk accessibility per cell subclass across donors spanning the full range of Alzheimer's disease neuropathological change, from middle temporal gyrus and prefrontal cortex; tracks colored by SEA-AD subclass.

The steps used to assemble the files into this track are recorded in the makeDoc.

Data Access

The subtracks can be explored in table form with the Table Browser or the Data Integrator, and read from scripts through our API.

For automated download and analysis, the signal and peak files are stored under http://hgdownload.soe.ucsc.edu/gbdb/hg38/bbi/singleCellSignalsPeaks/, keeping the same per-dataset subdirectories shown on the configuration page. The files can be read with the command-line tools bigWigToBedGraph (for the signal bigWigs) and bigBedToBed (for the peak files), which can be compiled from source or downloaded as precompiled binaries. Both take a region so you do not have to download the whole file, for example: 

bigWigToBedGraph -chrom=chr1 -start=1000000 -end=1100000 \
-  http://hgdownload.soe.ucsc.edu/gbdb/hg38/bbi/singleCellSignalsPeaks/neuro-degen-atac/bigWig/neuronal-celltypes/projNeuron_LDSCgroup-VIP_Interneurons_GRanges_insertions_bin100_RIPnorm.bw \
+  http://hgdownload.soe.ucsc.edu/gbdb/hg38/bbi/singleCellSignalsPeaks/cardiogenesis-atac/hub/in-vivo/Veins.bw \
   stdout
 
 bigBedToBed -chrom=chr21 -start=0 -end=48000000 \
-  http://hgdownload.soe.ucsc.edu/gbdb/hg38/bbi/singleCellSignalsPeaks/cortex-atac/hub/Enhancerpeaks/AstroOligo.bb \
+  http://hgdownload.soe.ucsc.edu/gbdb/hg38/bbi/singleCellSignalsPeaks/cortex-atac/hub/peaks.bb \
   stdout

The underlying matrices, metadata, and per-dataset download details are on each dataset's page in the UCSC Cell Browser.

Credits

Thanks to the UCSC Cell Browser team and the research groups whose single-cell datasets are shown here. Questions about a particular subtrack are best directed to the dataset page it links to.

References

Zhang K, Hocker JD, Miller M, Hou X, Chiou J, Poirion OB, Qiu Y, Li YE, Gaulton KJ, Wang A et al. A single-cell atlas of chromatin accessibility in the human genome. Cell. 2021 Nov 24;184(24):5985-6001.e19. PMID: 34774128; PMC: PMC8664161

Ziffra RS, Kim CN, Ross JM, Wilfert A, Turner TN, Haeussler M, Casella AM, Przytycki PF, Keough KC, Shin D et al. Single-cell epigenomics reveals mechanisms of human cortical development. Nature. 2021 Oct;598(7879):205-213. PMID: 34616060; PMC: PMC8494642

Li J, Wang J, Ibarra IL, Cheng X, Luecken MD, Lu J, Monavarfeshani A, Yan W, Zheng Y, Zuo Z et al. Integrated multi-omics single cell atlas of the human retina. bioRxiv. 2023 Nov 8.

Corces MR, Shcherbina A, Kundu S, Gloudemans MJ, Frésard L, Granja JM, Louie BH, Eulalio T, Shams S, Bagdatli ST et al. Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer's and Parkinson's diseases. Nat Genet. 2020 Nov;52(11):1158-1168. PMID: 33106633; PMC: PMC7606627

Gao W, Hu P, Wick B, Qiu Q, Zhang H, Li Y, Kang X, Bedi K, Haeussler M, Sasaki K et al. An integrative single-nucleus multiomic atlas of the human left ventricle identifies gene regulatory network dynamics across cardiac development, aging, and disease. Genome Biol. 2026 Apr 6;27(1). PMID: 41937210; PMC: PMC13067603

Ameen M, Sundaram L, Shen M, Banerjee A, Kundu S, Nair S, Shcherbina A, Gu M, Wilson KD, Varadarajan A et al. Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non- coding mutations in congenital heart disease. Cell. 2022 Dec 22;185(26):4937-4953.e23. PMID: 36563664; PMC: PMC10122433

Meijer M, Agirre E, Kabbe M, van Tuijn CA, Heskol A, Zheng C, Mendanha Falcão A, Bartosovic M, Kirby L, Calini D et al. Epigenomic priming of immune genes implicates oligodendroglia in multiple sclerosis susceptibility. Neuron. 2022 Apr 6;110(7):1193-1210.e13. PMID: 35093191; PMC: PMC9810341

Gabitto MI, Travaglini KJ, Rachleff VM, Kaplan ES, Long B, Ariza J, Ding Y, Mahoney JT, Dee N, Goldy J et al. Integrated multimodal cell atlas of Alzheimer's disease. Nat Neurosci. 2024 Dec;27(12):2366-2383. PMID: 39402379; PMC: PMC11614693

Hawrylycz M, Kaplan ES, Travaglini KJ, Gabitto MI, Miller JA, Ng L, Close JL, Hodge RD, Long B, Mollenkopf T et al. SEA-AD is a multimodal cellular atlas and resource for Alzheimer's disease. Nat Aging. 2024 Oct;4(10):1331-1334. PMID: 39402332; PMC: PMC11577961