38d5c1e91f3a867c589da441f549c9d46bc9b9f4 mspeir Mon Jul 20 14:05:31 2026 -0700 Add singleCellSignalsPeaks track to hg38 Native faceted composite built from the per-cell-type signal (bigWig) and peak (bigBed/bigNarrowPeak) tracks of the UCSC Cell Browser single-cell ATAC datasets, re-parented under one track in the regulation group. 936 subtracks across 9 datasets. Data files live in /hive/data/genomes/hg38/bed/singleCellSignalsPeaks and are served via a /gbdb/hg38/bbi symlink; the .ra is regenerated from the Cell Browser hub build by makeDb/scripts/singleCellSignalsPeaks/makeSingleCellSignalsPeaksRa.py. refs #37820 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> diff --git src/hg/makeDb/trackDb/human/hg38/singleCellSignalsPeaks.html src/hg/makeDb/trackDb/human/hg38/singleCellSignalsPeaks.html new file mode 100644 index 00000000000..f7150229478 --- /dev/null +++ src/hg/makeDb/trackDb/human/hg38/singleCellSignalsPeaks.html @@ -0,0 +1,266 @@ +<h2>Description</h2> +<p> +This track collects the cell-type chromatin accessibility tracks from the +single-cell ATAC-seq datasets in the +<a href="https://cells.ucsc.edu" target="_blank">UCSC Cell Browser</a>. 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. +</p> +<p> +The subtracks come from these datasets: +</p> +<ul> + <li> + <b><a href="https://cells.ucsc.edu/?ds=human-enhancer-atlas" target="_blank">Human Enhancer Atlas</a></b>: + chromatin accessibility across 30 adult and 15 fetal human tissue types, + describing about 1.2 million candidate cis-regulatory elements in 222 cell + types. 222 signal and 222 peak subtracks (Zhang et al. 2021). + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=cortex-atac" target="_blank">Cortex ATAC</a></b>: + single-cell epigenomes of the developing human brain and cortical + organoids. 12 signal and 79 peak subtracks (Ziffra et al. 2021). + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=retina" target="_blank">Human and Mouse Retina Cell Atlas</a></b>: + accessibility across retinal cell types. 39 signal and 30 peak subtracks + (Li et al. 2023, preprint). + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=neuro-degen-atac" target="_blank">Risk Loci in Alzheimer's and Parkinson's</a></b>: + accessibility of six adult human brain regions, defining 359,022 cell + type-specific regulatory elements used to interpret disease-associated + variants. 65 signal and 2 peak subtracks (Corces et al. 2020). + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=multiomic-human-heart" target="_blank">Multiomic Human Heart</a></b>: + accessibility across human cardiac development, aging, and disease, paired + with expression data. 40 signal subtracks (Gao et al. 2026). + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=cardiogenesis-atac" target="_blank">Human Cardiogenesis</a></b>: + accessibility of human fetal hearts at three early developmental stages, + used to prioritize noncoding variants in congenital heart disease. 19 + signal subtracks (Ameen et al. 2022). + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=olg-eae-ms" target="_blank">Oligodendrocytes in Mouse EAE Model of MS</a></b>: + accessibility in the oligodendrocyte lineage; the tracks here are the + accessibility measured in oligodendroglia from adult human brain. 18 signal + subtracks (Meijer et al. 2022). + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=brainvar+gene-activity" target="_blank">BrainVar</a></b>: + gene-activity signal from snATAC-seq of prenatal dorsolateral prefrontal + cortex. 4 signal subtracks. + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=sea-ad-mtg+cohort" target="_blank">SEA-AD Brain ATAC</a></b>: + chromatin accessibility per cell subclass across the spectrum of Alzheimer's + disease neuropathological change, from middle temporal gyrus and prefrontal + cortex; tracks are colored by SEA-AD subclass. 184 signal subtracks + (Gabitto et al. 2024). + </li> +</ul> + +<h2>Display Conventions and Configuration</h2> +<p> +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. +</p> + +<h2>Methods</h2> +<p> +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. +</p> +<table class="stdTbl"> + <tr><th>Dataset</th><th>Assay</th><th>Processing summary</th></tr> + <tr> + <td>Human Enhancer Atlas</td> + <td>single-cell ATAC-seq (adult and fetal tissues)</td> + <td>Accessibility profiled across 30 adult and 15 fetal tissues, integrated to call about 1.2 million candidate cis-regulatory elements across 222 cell types.</td> + </tr> + <tr> + <td>Cortex ATAC</td> + <td>10x single-cell ATAC-seq</td> + <td>Developing human cortex and organoid nuclei clustered by accessibility; gene-activity signal derived from accessibility near genes.</td> + </tr> + <tr> + <td>Human and Mouse Retina Cell Atlas</td> + <td>single-nucleus ATAC-seq</td> + <td>Retinal nuclei clustered into cell types, with per-cell-type coverage and peak calls.</td> + </tr> + <tr> + <td>Risk Loci in Alzheimer's and Parkinson's</td> + <td>10x single-cell ATAC-seq</td> + <td>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.</td> + </tr> + <tr> + <td>Multiomic Human Heart</td> + <td>single-nucleus ATAC-seq (with snRNA-seq)</td> + <td>106 snATAC datasets processed with SnapATAC2, batch-corrected by donor and study, integrated with expression from 299 donors.</td> + </tr> + <tr> + <td>Human Cardiogenesis</td> + <td>single-cell ATAC-seq</td> + <td>Human fetal hearts from three early stages profiled to map dynamic regulatory elements across cardiac differentiation trajectories.</td> + </tr> + <tr> + <td>Oligodendrocytes in Mouse EAE Model of MS</td> + <td>single-cell ATAC-seq</td> + <td>Accessibility of the oligodendrocyte lineage; the human tracks show accessibility in oligodendroglia from adult human brain.</td> + </tr> + <tr> + <td>BrainVar</td> + <td>single-nucleus ATAC-seq</td> + <td>Prenatal dorsolateral prefrontal cortex nuclei summarized as gene-activity coverage per major cell class.</td> + </tr> + <tr> + <td>SEA-AD Brain ATAC</td> + <td>single-nucleus ATAC-seq</td> + <td>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.</td> + </tr> +</table> +<p> +The steps used to assemble the files into this track are recorded in the +<a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/singleCellSignalsPeaks.txt" target="_blank">makeDoc</a>. +</p> + +<h2>Data Access</h2> +<p> +The subtracks can be explored in table form with the +<a href="hgTables">Table Browser</a> or the +<a href="hgIntegrator">Data Integrator</a>, and read from scripts through our +<a href="https://api.genome.ucsc.edu" target="_blank">API</a>. +</p> +<p> +For automated download and analysis, the signal and peak files are stored under +<a href="http://hgdownload.soe.ucsc.edu/gbdb/hg38/bbi/singleCellSignalsPeaks/" target="_blank">http://hgdownload.soe.ucsc.edu/gbdb/hg38/bbi/singleCellSignalsPeaks/</a>, +keeping the same per-dataset subdirectories shown on the configuration page. The +files can be read with the command-line tools <tt>bigWigToBedGraph</tt> (for the +signal bigWigs) and <tt>bigBedToBed</tt> (for the peak files), which can be +compiled from source or downloaded as +<a href="http://hgdownload.soe.ucsc.edu/downloads.html#utilities_downloads" target="_blank">precompiled binaries</a>. +Both take a region so you do not have to download the whole file, for example: +</p> +<pre><code>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 \ + stdout + +bigBedToBed -chrom=chr21 -start=0 -end=48000000 \ + http://hgdownload.soe.ucsc.edu/gbdb/hg38/bbi/singleCellSignalsPeaks/cortex-atac/hub/Enhancerpeaks/AstroOligo.bb \ + stdout</code></pre> +<p> +The underlying matrices, metadata, and per-dataset download details are on each +dataset's page in the <a href="https://cells.ucsc.edu" target="_blank">UCSC Cell +Browser</a>. +</p> + +<h2>Credits</h2> +<p> +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. +</p> + +<h2>References</h2> + +<p> +Zhang K, Hocker JD, Miller M, Hou X, Chiou J, Poirion OB, Qiu Y, Li YE, Gaulton KJ, Wang A <em>et +al</em>. +<a href="https://linkinghub.elsevier.com/retrieve/pii/S0092-8674(21)01279-4" target="_blank"> +A single-cell atlas of chromatin accessibility in the human genome</a>. +<em>Cell</em>. 2021 Nov 24;184(24):5985-6001.e19. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/34774128" target="_blank">34774128</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8664161/" target="_blank">PMC8664161</a> +</p> + +<p> +Ziffra RS, Kim CN, Ross JM, Wilfert A, Turner TN, Haeussler M, Casella AM, Przytycki PF, Keough KC, +Shin D <em>et al</em>. +<a href="https://doi.org/10.1038/s41586-021-03209-8" target="_blank"> +Single-cell epigenomics reveals mechanisms of human cortical development</a>. +<em>Nature</em>. 2021 Oct;598(7879):205-213. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/34616060" target="_blank">34616060</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494642/" target="_blank">PMC8494642</a> +</p> + +<p> +Li J, Wang J, Ibarra IL, Cheng X, Luecken MD, Lu J, Monavarfeshani A, Yan W, Zheng Y, Zuo Z <em>et +al</em>. +<a href="https://www.biorxiv.org/content/10.1101/2023.11.07.566105v1" target="_blank"> +Integrated multi-omics single cell atlas of the human retina</a>. +<em>bioRxiv</em>. 2023 Nov 8. +</p> + +<p> +Corces MR, Shcherbina A, Kundu S, Gloudemans MJ, Frésard L, Granja JM, Louie BH, Eulalio T, Shams S, +Bagdatli ST <em>et al</em>. +<a href="https://doi.org/10.1038/s41588-020-00721-x" target="_blank"> +Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for +Alzheimer's and Parkinson's diseases</a>. +<em>Nat Genet</em>. 2020 Nov;52(11):1158-1168. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/33106633" target="_blank">33106633</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7606627/" target="_blank">PMC7606627</a> +</p> + +<p> +Gao W, Hu P, Wick B, Qiu Q, Zhang H, Li Y, Kang X, Bedi K, Haeussler M, Sasaki K <em>et al</em>. +<a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-026-04061-7" target="_blank"> +An integrative single-nucleus multiomic atlas of the human left ventricle identifies gene regulatory +network dynamics across cardiac development, aging, and disease</a>. +<em>Genome Biol</em>. 2026 Apr 6;27(1). +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/41937210" target="_blank">41937210</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13067603/" target="_blank">PMC13067603</a> +</p> + +<p> +Ameen M, Sundaram L, Shen M, Banerjee A, Kundu S, Nair S, Shcherbina A, Gu M, Wilson KD, Varadarajan +A <em>et al</em>. +<a href="https://linkinghub.elsevier.com/retrieve/pii/S0092-8674(22)01503-3" target="_blank"> +Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non- +coding mutations in congenital heart disease</a>. +<em>Cell</em>. 2022 Dec 22;185(26):4937-4953.e23. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/36563664" target="_blank">36563664</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10122433/" target="_blank">PMC10122433</a> +</p> + +<p> +Meijer M, Agirre E, Kabbe M, van Tuijn CA, Heskol A, Zheng C, Mendanha Falcão A, Bartosovic M, Kirby +L, Calini D <em>et al</em>. +<a href="https://linkinghub.elsevier.com/retrieve/pii/S0896-6273(21)01089-8" target="_blank"> +Epigenomic priming of immune genes implicates oligodendroglia in multiple sclerosis +susceptibility</a>. +<em>Neuron</em>. 2022 Apr 6;110(7):1193-1210.e13. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/35093191" target="_blank">35093191</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9810341/" target="_blank">PMC9810341</a> +</p> + +<p> +Gabitto MI, Travaglini KJ, Rachleff VM, Kaplan ES, Long B, Ariza J, Ding Y, Mahoney JT, Dee N, Goldy +J <em>et al</em>. +<a href="https://doi.org/10.1038/s41593-024-01774-5" target="_blank"> +Integrated multimodal cell atlas of Alzheimer's disease</a>. +<em>Nat Neurosci</em>. 2024 Dec;27(12):2366-2383. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/39402379" target="_blank">39402379</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11614693/" target="_blank">PMC11614693</a> +</p> + +<p> +Hawrylycz M, Kaplan ES, Travaglini KJ, Gabitto MI, Miller JA, Ng L, Close JL, Hodge RD, Long B, +Mollenkopf T <em>et al</em>. +<a href="https://doi.org/10.1038/s43587-024-00719-8" target="_blank"> +SEA-AD is a multimodal cellular atlas and resource for Alzheimer's disease</a>. +<em>Nat Aging</em>. 2024 Oct;4(10):1331-1334. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/39402332" target="_blank">39402332</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11577961/" target="_blank">PMC11577961</a> +</p>