0abed78024d40b506c2b2e3a49ad483045bc5e1d mspeir Sat Aug 1 20:53:25 2026 -0700 singleCellSignalsPeaks: add native mm10 track mm10 counterpart of the hg38 track: 629 single-cell ATAC signal (bigWig) and peak (bigNarrowPeak) subtracks from 9 Cell Browser datasets, re-parented under one faceted composite in the regulation group. Colored by broad cell class from the same palette as hg38, grouped by class, off by default; cell types are paper-curated and the facets/longLabels are harmonized (see the makeDoc). Data lives in /hive/data/genomes/mm10/bed/singleCellSignalsPeaks and is served via the /gbdb/mm10/bbi symlink; the .ra is regenerated by makeSingleCellSignalsPeaksRa.py from the Cell Browser hub build. Included in mm10 trackDb.ra (alpha). refs #37914 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> diff --git src/hg/makeDb/trackDb/mouse/mm10/singleCellSignalsPeaks.html src/hg/makeDb/trackDb/mouse/mm10/singleCellSignalsPeaks.html new file mode 100644 index 00000000000..0ebde372f3c --- /dev/null +++ src/hg/makeDb/trackDb/mouse/mm10/singleCellSignalsPeaks.html @@ -0,0 +1,318 @@ +<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 (bigNarrowPeak), split out by +cell type. The datasets cover several mouse tissues, including brain, kidney, +and choroid plexus. +</p> +<p> +The subtracks come from these datasets: +</p> +<ul> + <li> + <b><a href="https://cells.ucsc.edu/?ds=catlas-mouse-aging" target="_blank">CATLAS Mouse Aging Brain</a></b>: + chromatin accessibility across cell types of the aging mouse brain. 234 + signal subtracks (Zhang et al. 2022). + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=catlas-mouse-brain" target="_blank">CATLAS Adult Mouse Brain</a></b>: + chromatin accessibility across cell types of the adult mouse cerebrum. 160 + signal subtracks (Li et al. 2021). + </li> + <li> + <b><a href="https://brain-map.org/genetic-tools/genetic-tools-atlas" target="_blank">Allen Basal Ganglia ATAC</a></b>: + accessibility across basal ganglia cell types, merged by region and neuron + subtype, from the Allen Institute Genetic Tools Atlas. 131 signal subtracks. + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=olg-dyn-eae-multiome" target="_blank">Dynamic Responses of Oligodendroglia in EAE Mice</a></b>: + accessibility (the ATAC half of a single-cell multiome study) of + oligodendroglia across disease progression in a mouse model of multiple + sclerosis. 28 signal subtracks (Zheng et al. 2025). + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=mouse-lvcp-multiome" target="_blank">Mouse Lateral Ventricle Choroid Plexus Multi-omics</a></b>: + accessibility (the ATAC half of a multi-omics study) of the lateral + ventricle choroid plexus, with per-cell-type peak calls. 17 signal and 6 + peak subtracks. + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=catlas-paired-tag" target="_blank">CATLAS Adult Mouse Brain Paired-Tag</a></b>: + the accessibility tracks from joint histone-and-transcriptome Paired-Tag + profiling of the adult mouse brain. 21 signal subtracks (Zhu et al. 2021). + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=mouse-kidney-atac" target="_blank">Mouse Kidney Regulatory Landscape</a></b>: + single-cell accessibility across mouse kidney cell types, used to map + cellular differentiation programs and disease-associated regulatory + regions. 19 signal subtracks (Miao et al. 2021). + </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 from a mouse model of multiple + sclerosis. 16 signal subtracks (Meijer et al. 2022). + </li> + <li> + <b><a href="https://cells.ucsc.edu/?ds=mouse-epi-juv-brain" target="_blank">Multimodal Chromatin Profiling of Juvenile Mouse Brain</a></b>: + accessibility from nanobody-based single-cell CUT&Tag multimodal + profiling of the juvenile mouse brain. 15 signal subtracks (Bartosovic and + Castelo-Branco 2023). + </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> + +<p> +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 human track). The classes are: +</p> +<table class="stdTbl"> + <tr><th style="background-color:rgb(0,114,178);width:2em"> </th> + <td>Excitatory neuron — glutamatergic neurons of the cortical layers, hippocampal CA fields and dentate gyrus, and claustrum</td></tr> + <tr><th style="background-color:rgb(213,94,0);width:2em"> </th> + <td>Inhibitory neuron — GABAergic neurons and interneurons (Pvalb, Sst, Lamp5, and CGE- and MGE-derived types)</td></tr> + <tr><th style="background-color:rgb(230,159,0);width:2em"> </th> + <td>Medium spiny neuron — striatal D1 and D2 projection neurons of the direct and indirect pathways</td></tr> + <tr><th style="background-color:rgb(86,180,233);width:2em"> </th> + <td>Other neuron — remaining neuronal types, such as Cajal-Retzius cells</td></tr> + <tr><th style="background-color:rgb(51,34,136);width:2em"> </th> + <td>Neural progenitor — neuroblasts, radial glia, and nephron progenitors</td></tr> + <tr><th style="background-color:rgb(0,158,115);width:2em"> </th> + <td>Astrocyte — astrocytes, including Bergmann glia and fibrous and protoplasmic subtypes</td></tr> + <tr><th style="background-color:rgb(204,121,167);width:2em"> </th> + <td>Oligodendrocyte — oligodendrocytes across the newly-formed, myelin-forming, and mature stages</td></tr> + <tr><th style="background-color:rgb(240,228,66);width:2em"> </th> + <td>Oligodendrocyte precursor — oligodendrocyte precursor cells (OPCs) and committed precursors</td></tr> + <tr><th style="background-color:rgb(0,0,0);width:2em"> </th> + <td>Microglia — microglia and perivascular macrophages</td></tr> + <tr><th style="background-color:rgb(68,170,153);width:2em"> </th> + <td>Ependymal — ependymal cells lining the ventricles</td></tr> + <tr><th style="background-color:rgb(136,34,85);width:2em"> </th> + <td>Choroid plexus — choroid plexus epithelial cells</td></tr> + <tr><th style="background-color:rgb(136,204,238);width:2em"> </th> + <td>Endothelial — endothelial cells of arteries, capillaries, veins, and endocardium</td></tr> + <tr><th style="background-color:rgb(221,204,119);width:2em"> </th> + <td>Mural — pericytes, smooth muscle, and vascular leptomeningeal cells</td></tr> + <tr><th style="background-color:rgb(238,102,119);width:2em"> </th> + <td>Immune — lymphoid (B, T) and myeloid (macrophage, dendritic, basophil) immune cells</td></tr> + <tr><th style="background-color:rgb(170,68,153);width:2em"> </th> + <td>Erythroid — erythroid cells and erythroblasts</td></tr> + <tr><th style="background-color:rgb(153,153,51);width:2em"> </th> + <td>Hematopoietic stem/progenitor — hematopoietic stem and progenitor cells</td></tr> + <tr><th style="background-color:rgb(170,68,0);width:2em"> </th> + <td>Cardiomyocyte — heart muscle cells</td></tr> + <tr><th style="background-color:rgb(102,17,0);width:2em"> </th> + <td>Muscle — skeletal muscle myofibers, satellite cells, and junctional myonuclei</td></tr> + <tr><th style="background-color:rgb(17,119,51);width:2em"> </th> + <td>Epithelial — epithelial cells of many tissues, such as airway, gut, kidney tubule, and secretory epithelia</td></tr> + <tr><th style="background-color:rgb(153,79,0);width:2em"> </th> + <td>Stromal — fibroblasts, mesenchymal, and other stromal cells</td></tr> + <tr><th style="background-color:rgb(153,153,153);width:2em"> </th> + <td>Other — other or mixed cell types, such as olfactory ensheathing cells and melanocytes</td></tr> + <tr><th style="background-color:rgb(187,187,187);width:2em"> </th> + <td>Unknown — cell type not resolved from the source data</td></tr> +</table> + +<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>CATLAS Mouse Aging Brain</td> + <td>single-cell ATAC-seq</td> + <td>Accessibility profiled across cell types of the aging mouse brain; per-cell-type coverage tracks.</td> + </tr> + <tr> + <td>CATLAS Adult Mouse Brain</td> + <td>single-cell ATAC-seq</td> + <td>Adult mouse cerebrum nuclei clustered into cell types, with per-cell-type accessibility coverage.</td> + </tr> + <tr> + <td>Allen Basal Ganglia ATAC</td> + <td>single-nucleus ATAC-seq</td> + <td>Basal ganglia nuclei grouped by region and neuron subtype (e.g. D1/D2 MSNs, dorsal/ventral), coverage per group.</td> + </tr> + <tr> + <td>Dynamic Responses of Oligodendroglia in EAE Mice</td> + <td>single-cell multiome (ATAC + RNA)</td> + <td>Oligodendroglia profiled across EAE disease progression; the ATAC arm gives per-cell-type accessibility coverage.</td> + </tr> + <tr> + <td>Mouse Lateral Ventricle Choroid Plexus Multi-omics</td> + <td>single-cell multiome (ATAC + RNA)</td> + <td>Choroid plexus nuclei profiled by multi-omics; ATAC arm gives per-cell-type coverage plus peak calls.</td> + </tr> + <tr> + <td>CATLAS Adult Mouse Brain Paired-Tag</td> + <td>Paired-Tag (histone + RNA)</td> + <td>Joint histone-modification and transcriptome profiling of adult mouse brain; the accessibility tracks are shown here.</td> + </tr> + <tr> + <td>Mouse Kidney Regulatory Landscape</td> + <td>single-cell ATAC-seq</td> + <td>Mouse kidney nuclei clustered into cell types; per-cell-type accessibility used to map differentiation programs and disease-relevant regulatory regions.</td> + </tr> + <tr> + <td>Oligodendrocytes in Mouse EAE Model of MS</td> + <td>single-cell ATAC-seq</td> + <td>Accessibility of the oligodendrocyte lineage in a mouse EAE model of multiple sclerosis.</td> + </tr> + <tr> + <td>Multimodal Chromatin Profiling of Juvenile Mouse Brain</td> + <td>nanobody-based single-cell CUT&Tag</td> + <td>Multimodal single-cell chromatin profiling of juvenile mouse brain; the accessibility tracks are shown here.</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/mm10/singleCellSignalsPeaks.txt" target="_blank">makeDoc</a>, +which uses the scripts in the +<a href="https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/scripts/singleCellSignalsPeaks" target="_blank">singleCellSignalsPeaks</a> +directory. +</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/mm10/bbi/singleCellSignalsPeaks/" target="_blank">http://hgdownload.soe.ucsc.edu/gbdb/mm10/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=3000000 -end=3100000 \ + http://hgdownload.soe.ucsc.edu/gbdb/mm10/bbi/singleCellSignalsPeaks/mouse-epi-juv-brain/hub/atac/BG.bw \ + stdout + +bigBedToBed -chrom=chr19 -start=0 -end=61000000 \ + http://hgdownload.soe.ucsc.edu/gbdb/mm10/bbi/singleCellSignalsPeaks/mouse-lvcp-multiome/scMultiome/atac/hub/peaks/all_cells.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 Y, Amaral ML, Zhu C, Grieco SF, Hou X, Lin L, Buchanan J, Tong L, Preissl S, Xu X <em>et +al</em>. +<a href="https://doi.org/10.1038/s41422-022-00719-6" target="_blank"> +Single-cell epigenome analysis reveals age-associated decay of heterochromatin domains in excitatory +neurons in the mouse brain</a>. +<em>Cell Res</em>. 2022 Nov;32(11):1008-1021. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/36207411" target="_blank">36207411</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9652396/" target="_blank">PMC9652396</a> +</p> + + + + +<p> +Li YE, Preissl S, Hou X, Zhang Z, Zhang K, Qiu Y, Poirion OB, Li B, Chiou J, Liu H <em>et al</em>. +<a href="https://doi.org/10.1038/s41586-021-03604-1" target="_blank"> +An atlas of gene regulatory elements in adult mouse cerebrum</a>. +<em>Nature</em>. 2021 Oct;598(7879):129-136. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/34616068" target="_blank">34616068</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494637/" target="_blank">PMC8494637</a> +</p> + + + + +<p> +Zheng C, Hervé B, Meijer M, Rubio Rodríguez-Kirby LA, Guerreiro Cacais AO, Kukanja P, Kabbe M, +Jimenez-Beristain T, Olsson T, Agirre E <em>et al</em>. +<a href="https://doi.org/10.1038/s41593-025-02100-3" target="_blank"> +Distinct transcriptomic and epigenomic responses of mature oligodendrocytes during disease +progression in a mouse model of multiple sclerosis</a>. +<em>Nat Neurosci</em>. 2025 Dec;28(12):2612-2627. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/41249698" target="_blank">41249698</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12672374/" target="_blank">PMC12672374</a> +</p> + + + + +<p> +Zhu C, Zhang Y, Li YE, Lucero J, Behrens MM, Ren B. +<a href="https://doi.org/10.1038/s41592-021-01060-3" target="_blank"> +Joint profiling of histone modifications and transcriptome in single cells from mouse brain</a>. +<em>Nat Methods</em>. 2021 Mar;18(3):283-292. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/33589836" target="_blank">33589836</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7954905/" target="_blank">PMC7954905</a> +</p> + + + + +<p> +Miao Z, Balzer MS, Ma Z, Liu H, Wu J, Shrestha R, Aranyi T, Kwan A, Kondo A, Pontoglio M <em>et +al</em>. +<a href="https://doi.org/10.1038/s41467-021-22266-1" target="_blank"> +Single cell regulatory landscape of the mouse kidney highlights cellular differentiation programs +and disease targets</a>. +<em>Nat Commun</em>. 2021 Apr 15;12(1):2277. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/33859189" target="_blank">33859189</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050063/" target="_blank">PMC8050063</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> +Bartosovic M, Castelo-Branco G. +<a href="https://doi.org/10.1038/s41587-022-01535-4" target="_blank"> +Multimodal chromatin profiling using nanobody-based single-cell CUT&Tag</a>. +<em>Nat Biotechnol</em>. 2023 Jun;41(6):794-805. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/36536148" target="_blank">36536148</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10264246/" target="_blank">PMC10264246</a> +</p> +