b914d581f876d486caf9404e715e4f61ada38195
mspeir
  Mon Aug 3 16:19:44 2026 -0700
singleCellSignalsPeaks: make every subtrack label unique, fix cell-class regressions

The harmonized labels were not distinguishing tracks. build_long_label composed from
cell type + condition + tissue, but the upstream steps discard the discriminators on
purpose to keep the facets compact, so hg38 had 925 subtracks sharing only 401 distinct
longLabels and mm10 629 sharing 359. Worst case: cortex-atac's MACS, enhancer and
cell-type-specific peak sets all read "Astrocytes and oligodendrocytes (Cortex ATAC)",
with the peak method surviving only in the raw shortLabel.

Labels are now built from the harmonized cell type plus a variant descriptor that
recovers what was dropped (peak method, grouping level, cohort, signal vs peaks), and
anything still colliding is qualified with its source cluster code. shortLabels are
rebuilt too -- the old ones were raw source strings up to 50 chars with underscores,
ArchR filename tails and R-mangled names -- abbreviated through a curated word table to
22 chars, with compact tokens where the longLabel distinction would otherwise be
invisible (SEA-AD region + ADNC, CATLAS aging age). All 925/587 longLabels are now
unique; no shortLabel exceeds 22 chars or contains an underscore.

Also fixed, found while verifying the above:

- Correcting source misspellings in the cell types broke the curated lookups, which are
keyed on those same misspelled strings, and 16 hg38 tracks silently lost their
Cell_class and color. The class map and the hub_config tables now normalize their keys
on load, and a cell type with no broad class is reported instead of becoming "unknown".
- Nephron progenitor was classed as Neural progenitor: the decode tables give it the bare
broad class "Progenitor" and that was blanket-mapped to neural. It is Six2+ kidney cap
mesenchyme, so it is now Stromal. The HTML legend had been worded to match the bug.
- The plural/case merge picked the most frequent form, which was inconsistent -- singular
for 15 of 17 merged groups but plural for Megakaryocytes/Oligodendrocytes. It now
prefers the singular.
- Removed 42 byte-identical Allen basal-ganglia bigWigs (md5-verified) that were served
from four grouping directories and rendered as four indistinguishable mm10 subtracks,
freeing 4.4 GB. Where the four copies genuinely differ all are kept and told apart by
the grouping-level descriptor. mm10 goes 629 -> 587 subtracks.
- Corrected five stale per-dataset subtrack counts in the description pages and spelled
out what ADNC means, noting that it grades neuropathology rather than symptoms.
- The SEA-AD Dataset facet link used the collection name, which is not a served Cell
Browser slug; it now points at sea-ad-mtg+cohort.
- Dropped a dead placeholder variable and made the hardcoded hub-build path overridable.

refs #37914

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

diff --git src/hg/makeDb/trackDb/human/hg38/singleCellSignalsPeaks.html src/hg/makeDb/trackDb/human/hg38/singleCellSignalsPeaks.html
index 50f2215eb6f..9ae0f7f1436 100644
--- src/hg/makeDb/trackDb/human/hg38/singleCellSignalsPeaks.html
+++ src/hg/makeDb/trackDb/human/hg38/singleCellSignalsPeaks.html
@@ -1,312 +1,323 @@
 <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;
     the study mapped about 1.2 million candidate cis-regulatory elements across
     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).
+    organoids. 12 signal and 69 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 across six adult human brain regions, with 359,022 cell
     type-specific regulatory elements used to interpret disease-associated
-    variants. 65 signal and 2 peak subtracks (Corces et al. 2020).
+    variants. 64 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>
 
+<p>
+Most subtracks are marked <em>Healthy</em> in the condition facet. The SEA-AD brain
+tracks instead carry an ADNC level, short for Alzheimer's disease neuropathological
+change. This is the NIA-AA score that combines the anatomical distribution of amyloid
+plaques (Thal phase), the stage of neurofibrillary tangle spread (Braak stage), and
+neuritic plaque density (CERAD) into four ordinal levels, shown here as ADNC 0 (no AD),
+ADNC 1 (low), ADNC 2 (intermediate), and ADNC 3 (high). ADNC grades neuropathology
+rather than symptoms: donors with high ADNC do not necessarily have dementia, and
+SEA-AD records cognitive status as a separate measure.
+</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 mouse track. The classes are:
 </p>
 <table class="stdTbl">
   <tr><th style="background-color:rgb(0,114,178);width:2em">&nbsp;</th>
       <td>Excitatory neuron &mdash; 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">&nbsp;</th>
       <td>Inhibitory neuron &mdash; 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">&nbsp;</th>
       <td>Medium spiny neuron &mdash; 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">&nbsp;</th>
       <td>Other neuron &mdash; remaining neuronal types, such as Cajal-Retzius cells</td></tr>
   <tr><th style="background-color:rgb(51,34,136);width:2em">&nbsp;</th>
-      <td>Neural progenitor &mdash; neuroblasts, radial glia, and nephron progenitors</td></tr>
+      <td>Neural progenitor &mdash; neuroblasts, radial glia, and other neural progenitors</td></tr>
   <tr><th style="background-color:rgb(0,158,115);width:2em">&nbsp;</th>
       <td>Astrocyte &mdash; astrocytes, including Bergmann glia and fibrous and protoplasmic subtypes</td></tr>
   <tr><th style="background-color:rgb(204,121,167);width:2em">&nbsp;</th>
       <td>Oligodendrocyte &mdash; oligodendrocytes across the newly-formed, myelin-forming, and mature stages</td></tr>
   <tr><th style="background-color:rgb(240,228,66);width:2em">&nbsp;</th>
       <td>Oligodendrocyte precursor &mdash; oligodendrocyte precursor cells (OPCs) and committed precursors</td></tr>
   <tr><th style="background-color:rgb(0,0,0);width:2em">&nbsp;</th>
       <td>Microglia &mdash; microglia and perivascular macrophages</td></tr>
   <tr><th style="background-color:rgb(136,204,238);width:2em">&nbsp;</th>
       <td>Endothelial &mdash; endothelial cells of arteries, capillaries, veins, and endocardium</td></tr>
   <tr><th style="background-color:rgb(221,204,119);width:2em">&nbsp;</th>
       <td>Mural &mdash; pericytes, smooth muscle, and vascular leptomeningeal cells</td></tr>
   <tr><th style="background-color:rgb(238,102,119);width:2em">&nbsp;</th>
       <td>Immune &mdash; lymphoid (B, T) and myeloid (macrophage, dendritic, basophil) immune cells</td></tr>
   <tr><th style="background-color:rgb(170,68,153);width:2em">&nbsp;</th>
       <td>Erythroid &mdash; erythroid cells and erythroblasts</td></tr>
   <tr><th style="background-color:rgb(153,153,51);width:2em">&nbsp;</th>
       <td>Hematopoietic stem/progenitor &mdash; hematopoietic stem and progenitor cells</td></tr>
   <tr><th style="background-color:rgb(170,68,0);width:2em">&nbsp;</th>
       <td>Cardiomyocyte &mdash; heart muscle cells</td></tr>
   <tr><th style="background-color:rgb(102,17,0);width:2em">&nbsp;</th>
       <td>Muscle &mdash; skeletal muscle myofibers, satellite cells, and junctional myonuclei</td></tr>
   <tr><th style="background-color:rgb(17,119,51);width:2em">&nbsp;</th>
       <td>Epithelial &mdash; 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">&nbsp;</th>
       <td>Stromal &mdash; fibroblasts, mesenchymal, and other stromal cells</td></tr>
   <tr><th style="background-color:rgb(153,153,153);width:2em">&nbsp;</th>
       <td>Other &mdash; 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">&nbsp;</th>
       <td>Unknown &mdash; 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>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/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/peaks.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>