444b1eb7e7ec2938a4a9a6d3ed214179073ab6f7 max Wed Sep 9 05:41:23 2026 -0700 Faceted composite: manual row reordering, group-by, saved UI state, and per-facet "only" links The Fiber-seq compendium put 41 samples times six data types into one faceted composite, which pushed on the parts of the page that were built for a flat list of tracks. Changes here, all in the shared faceted composite code rather than anything Fiber-seq specific: Row order. Track order in the image follows the table, so the table now lets you set that order by hand. Vendored DataTables RowReorder 1.5.1 adds a drag handle as the first column after the checkbox, enabled on the "shown in the browser" tab where reordering means something. The dragged order is remembered by sample name rather than by row number, so it survives a metadata file whose contents have changed. Group by. A container of six data types can be read two ways, so the page offers both: group the image by sample, keeping a sample's six tracks together, or by data type, putting all the accessibility tracks next to each other. cartDump assigns the priorities and just swaps the nesting of its two loops. trackDb sets the starting choice with defaultGroupBy. Saved state. Facets, per-column searches, sort column, page length, which tab was open and the hand-dragged order go to localStorage keyed by metadata id, so coming back to the page does not mean setting it all up again. Facet "only" links. A small "only" appears on hover behind each facet value and narrows to just that one, instead of unticking the others by hand. Column descriptions. A metadata column heading can now carry a longer explanation after a "|", shown behind an info icon on both the column header and the facet heading. Also: parseDataTypes() was returning its list reversed, since slPairAdd prepends and nothing put it back, so the data type checkboxes and the resulting subtrack order were backwards; the composite lifts itself out of hide when the user touches anything on the page, which is what they meant by touching it; the facet sidebar collapses when a table has no facetable columns; and the label wording throughout says "samples" and "in the browser" rather than "tracks" and "active". The Methbase hg38 track gets labels for its three data types, which were showing as the bare pipeline names hmr, levels and reads. refs #36210 diff --git src/hg/makeDb/trackDb/human/hg38/fiberSeqCompendium.html src/hg/makeDb/trackDb/human/hg38/fiberSeqCompendium.html index 9903fd79517..f0133557990 100644 --- src/hg/makeDb/trackDb/human/hg38/fiberSeqCompendium.html +++ src/hg/makeDb/trackDb/human/hg38/fiberSeqCompendium.html @@ -1,229 +1,233 @@ <h2>Description</h2> <p> This track holds the full Fiber-seq data for 41 samples: 14 cell lines and 27 lymphoblastoid lines derived from individuals sequenced by the Human Pangenome Reference Consortium and the Genome in a Bottle project. Chromatin accessibility and CpG methylation are read from the same molecules in the same experiment, so both are kept in one table here and can be compared without worrying about differences in cell preparation or sequencing depth. Six kinds of data are available for each sample: </p> <ul> <li>Percent accessible: the fraction of Fiber-seq molecules on which a position was called accessible, combining both chromosomes.</li> <li>FIRE peaks: the accessible regulatory elements called from that signal, with a score and a false discovery rate.</li> <li>Haplotype accessibility: the percent-accessible signal computed separately for the two parental chromosomes and drawn as an overlay, which makes elements that are open on one chromosome but not the other visible directly.</li> <li>CpG methylation: percent of reads methylated at each CpG, over both chromosomes.</li> <li>Haplotype CpG: the same measure computed separately for the two parental chromosomes.</li> <li>CpG haplotype difference: the difference in percent methylation between the two chromosomes, at four nested significance thresholds.</li> </ul> <p> Because 41 samples times six kinds of data is far too many tracks for a checkbox list, samples are chosen from a searchable table on this page. Pick the kinds of data you want along the top, then select samples in the table; the browser turns on that combination for every sample you -picked, and keeps each sample's tracks together in the display. The table can be filtered by -sample class, and searched or sorted by sample name, accession and cell type. Only sample class -offers filter checkboxes, because a checkbox is only useful when several samples share a value, -and the other three columns are close to unique per sample. +picked, and keeps each sample's tracks together in the display. Sample class has filter +checkboxes in the panel to the left, and every column can be searched with the box under its +heading and clicked to sort, so a sample can be found by name, cell type, sample class or +accession. </p> <h2>Display Conventions</h2> <p> Accessibility, methylation and the haplotype overlays are all drawn 0 to 100 percent on a fixed scale, so heights are comparable between samples and between the two assays. The accessibility tracks use maximum as the windowing function, so a narrow element survives zooming out, while the methylation tracks use mean, since an average is the meaningful summary for a methylation level. FIRE peaks are shown in dense mode by default, one row per sample. </p> <p> In both haplotype overlays: </p> <table class="stdTbl"> <tr><th style="background-color:#0072B2;width:2em"> </th><td>Haplotype 1</td></tr> <tr><th style="background-color:#D55E00;width:2em"> </th><td>Haplotype 2</td></tr> </table> <p> The two are overlaid transparently, so a position with equal signal on both chromosomes appears as the two colors superimposed, and a haplotype-selective element appears as one color standing alone. Which parental chromosome is haplotype 1 is arbitrary and is not consistent between samples. </p> <p> The CpG haplotype difference track runs from -100 to +100 percent, so a bar above the midline means haplotype 1 is more methylated and a bar below it means haplotype 2 is. It is a stack of four overlaid signals, one per significance threshold, drawn least significant first so that the more significant levels are painted on top: </p> <table class="stdTbl"> <tr><th style="background-color:#898F8F;width:2em"> </th><td>All measured differences, regardless of significance</td></tr> <tr><th style="background-color:#EBE534;width:2em"> </th><td>p < 0.01</td></tr> <tr><th style="background-color:#F59416;width:2em"> </th><td>p < 0.001</td></tr> <tr><th style="background-color:#FF0000;width:2em"> </th><td>p < 0.0001</td></tr> </table> <p> The thresholds are nested, so a position drawn red also belongs to all three looser sets. Reading the track amounts to reading the color: grey is noise, red is a strong difference between the two chromosomes at that CpG. </p> <p> -The color swatches next to the Sample class filters in the table are: +The color swatches next to the Sample class filters are: </p> <table class="stdTbl"> - <tr><th style="background-color:#0072B2;width:2em"> </th><td>Lymphoblastoid cell line</td></tr> - <tr><th style="background-color:#009E73;width:2em"> </th><td>Stem cell</td></tr> - <tr><th style="background-color:#D55E00;width:2em"> </th><td>Cancer or immortalized cell line</td></tr> + <tr><th style="background-color:#0072B2;width:2em"> </th> + <td>HPRC, a lymphoblastoid (B-lymphocyte, EBV) line from the Human Pangenome Reference + Consortium</td></tr> + <tr><th style="background-color:#D55E00;width:2em"> </th> + <td>Common cell line, which here also covers GM12878 and HG002: both are lymphoblastoid, + but they come from ENCODE and from Genome in a Bottle rather than from the + consortium</td></tr> </table> <p> Peaks carry two filterable values, the FIRE score in the signalValue field and the false discovery rate as a -log10 value in the qValue field, and both can be filtered from a peak track's own configuration page, along with the score. No filter is applied by default. A short tick inside each peak marks the point source, the single base the pipeline picked as the summit. Switching a peak track to pack or full also gives each peak a mouseover with its FIRE score and FDR; dense mode has no per-peak hover, which is a property of dense display rather than of this track. The pValue field of the source files is set to -1 throughout and carries no information. </p> <h2>Methods</h2> <p> Permeabilized cells were treated with the Hia5 N6-adenine methyltransferase, which methylates adenines in DNA not protected by a bound protein, and high molecular weight DNA was prepared into PacBio SMRTbell libraries and sequenced. The adenine methylation added by the enzyme is chemically distinct from native CpG methylation, so both are read from the same molecule. Adenine methylation was called with fibertools-rs v0.4, and reads were aligned and haplotype-phased; for GM12878 an average 20 kb read spans at least one heterozygous variant and 87.9 percent of reads could be phased against GRCh38. </p> <p> The FIRE pipeline v0.0.4, a Snakemake workflow, applied a semi-supervised XGBoost classifier to label methyltransferase-sensitive patches on each read as FIRE elements. The classifier was trained with Mokapot over 15 iterations on 21 GM12878 experiments spanning 5.8 to 13.3 percent adenine methylation, with DNase I and CTCF ChIP-seq peaks as mixed-positive labels. The aggregate FIRE score at a position is -50/R times the sum over covering elements of log10(1 - min(EP, 0.99)), where R is the read depth and EP the estimated precision of each element, which puts the score between 0 and 100; positions covered by fewer than four FIRE elements are not scored. The false discovery rate was estimated by shuffling whole reads within a chromosome and comparing the resulting score distribution to the observed one. Peaks are FIRE score local maxima below a 5 percent FDR with at least 10 percent of covering reads actuated; adjacent maxima sharing half their elements or overlapping reciprocally by 90 percent were merged, and peak boundaries were set to the median start and end of the underlying elements. </p> <p> Base-level CpG methylation was called with jasmine, and the percent methylation at each genomic position was computed from a pileup of reads using pb-CpG-tools. Reads were haplotype-phased before the pileup, which gives the per-haplotype values, and the difference track is the subtraction of one haplotype from the other with the per-position significance thresholds applied. See Vollger et al. for the full description of all of the above. </p> <p> The bigWig and bigBed files were downloaded from <a href="https://s3.kopah.uw.edu/userprod/web/public/hashed.PacBio-Fiber-seq/" target="_blank">the Stergachis lab data server</a>, eleven files per sample. The signal files were copied without modification. The peak files were rebuilt, because their bigBed header recorded three data columns while the data has the full ten of a narrowPeak file, which left the browser unable to see the signalValue and qValue columns for filtering or display. The rebuild corrects the header and rounds the FIRE score and the FDR to three decimals, which is well beyond the precision either measure carries. It does drop peaks called on chrEBV, the Epstein-Barr virus decoy of the GRCh38 analysis set, since that sequence is not part of hg38: 421 of 9,487,043 peaks, in 20 of the 41 samples, between 2 and 166 peaks each, leaving 9,486,622 in the track. The download, rebuild and integrity steps are documented in the <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/fiberSeq.txt" target="_blank">makeDoc</a>, and the scripts that fetch the data and generate the track configuration are in the <a href="https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/scripts/fiberSeq" target="_blank">kent source tree</a>. </p> <p> Two files are empty at the source: the haplotype accessibility bigWigs for GM12878 (accession PM00001), so its haplotype accessibility overlay shows no data. Its combined signal, its peaks and all of its CpG methylation are present, and every other sample has real haplotype files. </p> <h2>Data Access</h2> <p> The data can be explored interactively in table format with the <a href="../cgi-bin/hgTables">Table Browser</a> or the <a href="../cgi-bin/hgIntegrator">Data Integrator</a> and exported from there to spreadsheet or tab-sep tables. From scripts, the data can be accessed through our <a href="https://api.genome.ucsc.edu">API</a>, track=<i>fiberSeqCompendium</i>. </p> <p> For automated download and analysis, the data are stored in bigWig and bigBed files that can be downloaded from <a href="http://hgdownload.soe.ucsc.edu/gbdb/hg38/fiberSeq/" target="_blank">our download server</a>, one directory per sample accession. Each directory holds the peaks as <tt>fire-peaks.ucsc.bb</tt>, the accessibility signal as <tt>all.percent.accessible.bw</tt> with <tt>hap1.percent.accessible.bw</tt> and <tt>hap2.percent.accessible.bw</tt>, and the methylation as <tt>cpg.combined.bw</tt>, <tt>cpg.hap1.bw</tt>, <tt>cpg.hap2.bw</tt> and four <tt>cpg.diffs_*.bw</tt> files. Individual regions or the whole genome annotation can be obtained using our tools <tt>bigBedToBed</tt> and <tt>bigWigToBedGraph</tt>, which can be compiled from the source code or downloaded as precompiled binaries for your system. Instructions for downloading source code and binaries can be found <a href="http://hgdownload.soe.ucsc.edu/downloads.html#utilities_downloads">here</a>. The tools can also be used to obtain features within a given range, e.g. <tt>bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg38/fiberSeq/PM00001/fire-peaks.ucsc.bb -chrom=chr21 -start=0 -end=100000000 stdout</tt> </p> <p> The mapping from sample accession to sample name and cell type is in <a href="http://hgdownload.soe.ucsc.edu/gbdb/hg38/fiberSeq/fiberSeqCompendium_metadata.tsv" target="_blank">fiberSeqCompendium_metadata.tsv</a>. The original data can be downloaded from the <a href="https://s3.kopah.uw.edu/userprod/web/public/hashed.PacBio-Fiber-seq/" target="_blank">Stergachis lab data server</a>, and the lab maintains its own track hub and documentation at <a href="https://fiberseq.github.io/" target="_blank">fiberseq.github.io</a>. The FIRE pipeline is at <a href="https://github.com/fiberseq/FIRE" target="_blank">github.com/fiberseq/FIRE</a>, the adenine methylation caller at <a href="https://github.com/fiberseq/fibertools-rs" target="_blank">github.com/fiberseq/fibertools-rs</a>, and the CpG pileup tool at <a href="https://github.com/PacificBiosciences/pb-CpG-tools" target="_blank">github.com/PacificBiosciences/pb-CpG-tools</a>. </p> <h2>Credits</h2> <p> Thanks to Mitchell Vollger, Andrew Stergachis and Shane Neph for generating this data, for assembling it into track hubs and for their help in arranging these tracks for the browser. </p> <h2>References</h2> <p> Vollger MR, Swanson EG, Neph SJ, Ranchalis J, Munson KM, Ho CH, Cheng YHH, Sedeño-Cortés AE, Fondrie WE, Bohaczuk SC <em>et al</em>. <a href="https://doi.org/10.1101/2024.06.14.599122" target="_blank"> A haplotype-resolved view of human gene regulation</a>. <em>bioRxiv</em>. 2025 Jun 2;. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/40501892" target="_blank">40501892</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12157683/" target="_blank">PMC12157683</a> </p> <p> Stergachis AB, Debo BM, Haugen E, Churchman LS, Stamatoyannopoulos JA. <a href="https://www.ncbi.nlm.nih.gov/pubmed/32587015" target="_blank"> Single-molecule regulatory architectures captured by chromatin fiber sequencing</a>. <em>Science</em>. 2020 Jun 26;368(6498):1449-1454. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/32587015" target="_blank">32587015</a> </p>