ce780dd2f1216ce728ab6bb69ac19a39ddc694fd
max
  Tue Sep 8 00:26:39 2026 -0700
hg38: Fiber-seq container with accessibility, FIRE peaks and CpG methylation, 41 samples

Native version of the Stergachis/Vollger lab hub at
https://fiberseq.github.io/UCSC-Fiber-seq-hub/hub.txt, plus the per-sample CpG
methylation Shane Neph asked to have alongside it. Both cover the same 41
samples: 14 cell lines and 27 lymphoblastoid lines from HPRC and GIAB
individuals.

fiberSeq              container, group regulation
fiberSeqAcc         multiWig overlay of 7 common cell lines, on by default
fiberSeqCompendium  faceted composite, dataTypes acc/peaks/hap
fiberSeqMeth        faceted composite, dataTypes comb/hap/diffs, "Methylation"

Both composites use the Methbase faceted-composite machinery. Subtracks are
named <composite>_<accession>_<dataType> with the accession as the only middle
component, because facetedCompositeUi() cuts the data element at the first
underscore and cartDump.c reassembles the name from the pieces; the hub's
<composite>_<sample>_<accession>_<type> names would have resolved to tracks that
do not exist. Sample name and cell type live in the metadata TSV instead. Using
dataTypes also brings onlyVisibility, which is what lets the peaks default to
dense while the signal tracks default to full, the mixed-visibility default
Andrew Stergachis asked for.

397 GB mirrored from the UW Kopah S3 server rather than pointed at over the
network, since a native track should not depend on it.

The FIRE peak bigBeds had to be rebuilt: they carry full narrowPeak data but
their header records a field count of 3, which hides signalValue and qValue
from the browser and would have made hgTracks errAbort in
bigNarrowPeakLoadItems(). The rebuild fixes the header and rounds the two float
columns to 3 decimals, 467 MB to 313 MB. It drops 421 of 9,487,043 peaks called
on chrEBV, the EBV decoy of the GRCh38 analysis set, which hg38 does not have;
9,486,622 remain and every sample reconciles exactly. Reported upstream, along
with GM12878's two haplotype accessibility bigWigs, which are one-base
placeholders at the source.

refs #36210

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+<h2>Description</h2>
+
+<p>
+A methyl group on the cytosine of a CpG dinucleotide is a chemical mark that cells copy along
+with the DNA and use to keep genes switched off, most visibly at imprinted genes, where only the
+copy inherited from one parent is active, and on the inactive X chromosome. The PacBio instrument
+reports native CpG methylation from the same molecules used to measure chromatin accessibility,
+so this track and the <a href="hgTrackUi?g=fiberSeqCompendium">Fiber-seq Compendium</a> come from
+one experiment per sample and can be compared without worrying about differences in cell
+preparation or coverage.
+</p>
+
+<p>
+For each of the 41 samples three kinds of data are available:
+</p>
+
+<ul>
+  <li>Combined CpG: percent of reads methylated at each CpG, over both chromosomes.</li>
+  <li>Hap1/Hap2 CpG: the same measure computed separately for the two parental chromosomes.</li>
+  <li>Haplotype differences: the difference in percent methylation between the two chromosomes,
+      shown at four nested significance thresholds.</li>
+</ul>
+
+<p>
+Samples are chosen from a searchable table on this page. Pick the data types along the top, then
+select samples in the table.
+</p>
+
+<h2>Display Conventions</h2>
+
+<p>
+The combined and per-haplotype tracks are drawn 0 to 100 percent methylated with a fixed scale,
+using mean as the windowing function, since an average is the meaningful summary for a
+methylation level. In the haplotype overlay:
+</p>
+
+<table class="stdTbl">
+  <tr><th style="background-color:#0072B2;width:2em">&nbsp;</th><td>Haplotype 1</td></tr>
+  <tr><th style="background-color:#D55E00;width:2em">&nbsp;</th><td>Haplotype 2</td></tr>
+</table>
+
+<p>
+Which parental chromosome is haplotype 1 is arbitrary and is not consistent between samples.
+</p>
+
+<p>
+The 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">&nbsp;</th><td>All measured differences, regardless of significance</td></tr>
+  <tr><th style="background-color:#EBE534;width:2em">&nbsp;</th><td>p &lt; 0.01</td></tr>
+  <tr><th style="background-color:#F59416;width:2em">&nbsp;</th><td>p &lt; 0.001</td></tr>
+  <tr><th style="background-color:#FF0000;width:2em">&nbsp;</th><td>p &lt; 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>
+
+<h2>Methods</h2>
+
+<p>
+Permeabilized cells were treated with the Hia5 N6-adenine methyltransferase and sequenced as
+PacBio SMRTbell libraries; see the
+<a href="hgTrackUi?g=fiberSeqCompendium">Fiber-seq Compendium</a> track for the assay details.
+The adenine methylation added by the enzyme is chemically distinct from CpG methylation, so both
+are read from the same molecule. 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.
+</p>
+
+<p>
+The bigWig 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>, seven files per sample (<tt>cpg.combined.bw</tt>,
+<tt>cpg.hap1.bw</tt>, <tt>cpg.hap2.bw</tt>, <tt>cpg.diffs_all.bw</tt>,
+<tt>cpg.diffs_p0.01.bw</tt>, <tt>cpg.diffs_p0.001.bw</tt> and <tt>cpg.diffs_p0.0001.bw</tt>),
+and copied to UCSC without modification. The download 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>
+
+<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>fiberSeqMeth</i>.
+</p>
+
+<p>
+For automated download and analysis, the signal is stored in bigWig 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. The files for this track are the seven named
+above. Individual regions or the whole genome can be obtained using our tool
+<tt>bigWigToBedGraph</tt>, which can be compiled from the source code or downloaded as a
+precompiled binary 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
+tool can also be used to obtain values within a given range, e.g.
+<tt>bigWigToBedGraph http://hgdownload.soe.ucsc.edu/gbdb/hg38/fiberSeq/PM00001/cpg.combined.bw
+-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/fiberSeqMeth_metadata.tsv"
+target="_blank">fiberSeqMeth_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 methylation
+pileup tool is 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 Shane Neph, Mitchell Vollger and Andrew Stergachis for generating this data and for
+preparing the per-sample methylation hubs that this track was built from.
+</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://www.ncbi.nlm.nih.gov/pubmed/40501892" 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>
+