d07356d76401059fbe6c2d0890b1490546a62a4e max Mon Sep 14 02:54:50 2026 -0700 hg38 Fiber-seq: reissued GM12878 data and a nucleosome density track, refs #36210 The lab reprocessed GM12878 (PM00001) and replaced the files in place under the same hash directory. Ten of its twelve files changed; a size sweep over all 41 samples confirmed no other sample is affected. This fixes the two placeholder haplotype accessibility bigWigs that covered a single base, so that overlay now draws real data for the sample that comes up by default. Its peak calls changed substantially as well, 429,883 source peaks before and 196,742 now, which is noted on the description page since figures made from the first version of the track will not reproduce for GM12878. The downloader now fetches into <file>.part and moves it into place when complete. It used curl -C - straight onto the final file, which is right for an interrupted transfer and silently corrupting when the server has replaced the file: it would have appended the tail of the new 5.2 GB hap1 file to the 512-byte stub, and the size check afterwards would have passed. It also takes an optional list of accessions now, to refresh one sample without walking all 41. Nucleosome density (all.nucleosome.coverage.bw) was sent separately and is not in the lab's own hub. It is on the server for all 41 samples and is added as a seventh data type in the compendium. Unlike every other wiggle here it is a read depth rather than a percentage, so it cannot take fixed viewLimits: the genome-wide mean runs from 25 to 142 across samples with sequencing depth and single loci reach 1.7e5. It is drawn with autoScale, which the description page explains, and reads as the complement of the accessibility signal. diff --git src/hg/makeDb/trackDb/human/hg38/fiberSeqCompendium.html src/hg/makeDb/trackDb/human/hg38/fiberSeqCompendium.html index b85602a5be4..4197ce5a981 100644 --- src/hg/makeDb/trackDb/human/hg38/fiberSeqCompendium.html +++ src/hg/makeDb/trackDb/human/hg38/fiberSeqCompendium.html @@ -1,61 +1,73 @@ <h2>Description</h2> <p> This track is part of the <a href="hgTrackUi?g=fiberSeq">Fiber-seq</a> collection. It 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 +worrying about differences in cell preparation or sequencing depth. Seven 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>Nucleosome density: the number of Fiber-seq molecules on which a position was called as + covered by a nucleosome, that is, the complement of the accessible signal.</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 +Because 41 samples times seven 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. 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> +Nucleosome density is the exception to the fixed scale. It is a count of molecules rather than a +percentage, so its height depends on how deeply the sample was sequenced: the genome-wide mean +runs from 25 to 142 across these 41 samples, and a few loci reach into the hundred thousands. +It is therefore drawn with autoscaling, each window scaled to its own highest value, and the +numbers on the vertical axis are comparable within a sample but not between samples. Read it as +the shape against the accessibility signal of the same sample, where a nucleosome-depleted region +appears as a dip in this track under a peak in that one. +</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> @@ -104,76 +116,86 @@ 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> +Nucleosomes were called on each individual molecule from the same adenine methylation pattern: +a stretch of DNA long enough to wrap a nucleosome and carrying no methylation is inferred to +have been protected by one, and the stretches between them are the methyltransferase-sensitive +patches the FIRE classifier then scores. The nucleosome density track is the per-position count +of molecules whose nucleosome call covers that position, so it is a read depth and not a rate. +</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 +Stergachis lab data server</a>, twelve 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, +GRCh38 analysis set, since that sequence is not part of hg38: 309 of 9,253,902 peaks, in 20 of +the 41 samples, between 2 and 54 peaks each, leaving 9,253,593 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. +GM12878 (accession PM00001) was reprocessed by the lab in September 2026 and every file for that +sample was replaced here. The earlier release had two placeholder haplotype accessibility bigWigs +covering a single base, so its haplotype overlay drew nothing; those now carry full data. Its +peak calls and CpG haplotype values changed with the reprocessing as well, so figures made from +the first version of this track will not reproduce exactly for that sample. </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