d033cea2063e9362949baf5b4d8b837597173a0d
max
Thu Sep 10 05:16:05 2026 -0700
Address the code review of the Sep 9 commits
Faceted composite: text that comes from a hub - a metadata column's
description, the name and title of a data type, and the values quoted back in
the "could not load the metadata" row - is put on the page as text rather than
as markup. The three places built their markup from template strings, so a
value carrying angle brackets or a quote was read as HTML: the column
description now goes through the shared htmlEncode() once where the header is
parsed, and the other two build their elements as nodes. The error row reads
better for it as well, since a value with brackets in it used to disappear from
the message that was meant to show it.
The saved UI state keys on the assembly as well as the metadata id. localStorage
is per-origin, so two assemblies whose tracks share a name were sharing one
entry, and a row order dragged on one came back on the other over a different
set of samples. hgTrackUi passes the database down for it. State saved under the
old key is dropped, which costs a facet selection or a page length.
Imprinting: the five subtrack description pages link back to the container as
hgTrackUi?db=$db&g=$parentTrack, without the hgsid. Native trackDb html is
substituted by hgTrackDb as it loads the table, where there is no cart, so
${hgsid} came out empty and the link read 'hgsid=&g=...'. Matches what the
Fiber-seq pages already do. The makeDoc note that described the old form is
updated with the reason.
UniProt otto: README.txt lists all eight things that reach runLog.txt. It had
four, and was missing LOCKED, along with PREFLIGHT-FAIL, END and INTERRUPTED.
refs #36210
refs #37599
refs #38300
diff --git src/hg/makeDb/trackDb/human/hg38/akbariIdmr.html src/hg/makeDb/trackDb/human/hg38/akbariIdmr.html
index 6cda526d548..42a75d0d372 100644
--- src/hg/makeDb/trackDb/human/hg38/akbariIdmr.html
+++ src/hg/makeDb/trackDb/human/hg38/akbariIdmr.html
@@ -1,227 +1,227 @@
<h2>Description</h2>
<p>
-Part of the <a href="hgTrackUi?db=$db&hgsid=${hgsid}&g=$parentTrack">Imprinting</a> track collection, this track shows imprinted differentially methylated
+Part of the <a href="hgTrackUi?db=$db&g=$parentTrack">Imprinting</a> track collection, this track shows imprinted differentially methylated
regions, or iDMRs. Because the methylated copy of an iDMR is always the one from the same parent,
an iDMR is a fixed landmark that says which of a person's two chromosomes came from the mother and
which from the father, without sequencing the parents.
</p>
<p>
This track shows 192 such regions on the autosomes, assembled by Akbari et al.
(2023) from five earlier genome-wide surveys of imprinted methylation and used
by their PatMat method to assign whole chromosomes to a parent of origin. Just
under half of the regions were reported independently by two or more of the
five studies. The rest come from a single study and were kept only after they
showed the expected half-methylated signal in public methylomes from blood and
from many tissues. The X chromosome was left out, since it is not generally
thought to carry iDMRs.
</p>
<p>
The regions cover the classic imprinting control regions, including the H19
region and both IGF2 DMRs on chromosome 11, KvDMR1 at the KCNQ1 cluster, the
SNRPN region on chromosome 15, the IG-DMR and MEG3 regions on chromosome 14 and
both GNAS regions on chromosome 20, together with a long tail of less
well-established loci.
</p>
<h2>Display Conventions and Configuration</h2>
<p>
Each item is one region. Items are labeled with the first gene at or near the
region; the configuration page can switch the label to the full list of genes,
which is also shown when the mouse hovers over an item. The regions have no
meaningful strand.
</p>
<p>
The color shows which parental copy carries the methylation. Vermillion and
blue mean the maternal and the paternal copy on every subtrack of this
collection, but what is marked differs: this track marks the <em>methylated</em>
copy, while <a href="hgTrackUi?g=geneimprint">Geneimprint</a> marks the
<em>expressed</em> copy. At the H19 region this track is blue because the
paternal copy is the methylated one, and Geneimprint shows H19 in vermillion
because the maternal copy is the expressed one. Both are right. Note also that
methylation at an imprinting control region does not always silence the nearby
gene: the methylated paternal H19 region is what allows IGF2 to be expressed
from the paternal chromosome.
</p>
<table class="stdTbl">
<tr><th style="background-color:#D55E00;width:2em"> </th>
<td>Maternal — the copy inherited from the mother is methylated,
so it is the silenced copy (144 regions)</td></tr>
<tr><th style="background-color:#0072B2;width:2em"> </th>
<td>Paternal — the copy inherited from the father is methylated,
so it is the silenced copy (48 regions)</td></tr>
</table>
<p>
Three filters are available: methylated allele, evidence level (reported by
several studies or by one study plus confirmation in public methylomes), and
which of the five source studies reported the region. None of them filters
anything out by default.
</p>
<p>
Clicking a region opens a page with the methylated allele, the source studies,
and the counts behind the confirmation step: how many blood methylomes and how
many tissue methylomes could be tested at that region, and in how many of them
the region was partially methylated. One region, the H19 region on chromosome
11, has no counts in the published table, so those rows are left out on its
page.
</p>
<h2>Methods</h2>
<p>
Akbari et al. combined nanopore sequencing, which reads DNA methylation
directly off the same molecule as the sequence, with the long-range phase
information in Strand-seq data, to build chromosome-length haplotypes and then
assign each haplotype to a parent. Nanopore reads at 24 to 38-fold coverage
were base called with guppy and mapped to GRCh38 with minimap2, variants were
called with Clair3, and Strand-seq libraries at 2.8 to 9.5-fold combined
coverage were used to phase those variants across whole chromosomes. The parent
of origin then follows from the methylation state of the haplotypes at the
iDMRs. Tested on five trios with diverse genetic backgrounds, the method
assigned the parent of origin correctly for every autosome, with a mismatch
error rate of 0.31% for single-nucleotide variants and 1.89% for insertions and
deletions.
</p>
<p>
The region list itself was built as follows. Candidate iDMRs were gathered from
five earlier genome-wide studies (Court et al. 2014, Joshi et al. 2016,
Hernandez Mora et al. 2018, Zink et al. 2018 and Akbari et al. 2022). Regions
overlapping between two or more studies were merged into the largest interval
covered, and regions within 1 kb of each other with the same parent of origin
were also merged. This gave 93 regions seen in at least two studies and 306
seen in only one. The single-study regions were then filtered: first against
twelve nanopore-sequenced cell lines with trio information, dropping regions
whose parent of origin conflicted with the original report, and then against
whole-genome bisulfite data from 119 blood samples from 87 individuals in
Blueprint and 60 samples covering 29 tissue types from ENCODE and Roadmap. The
reasoning behind the second filter is that if only one allele of a region is
methylated, the two alleles together should read as about half methylated. A
region counted as partially methylated in a sample if it had at least five CpG
sites with at least five reads and more than 60% of those sites had a
methylation fraction between 0.35 and 0.65. Regions had to pass in at least two
samples and in at least 5% of the samples where they could be tested. That left
99 of the single-study regions, for 192 in total. As a control, randomly chosen
intervals passed the same criteria only 2.4% of the time.
</p>
<p>
The region list was taken from table S3 of the paper, which is also distributed
with the authors' PatMat software as
<tt>Imprinted_DMR_List_V1.GRCh38.tsv</tt> at
<a href="https://github.com/vahidAK/PatMat" target="_blank">https://github.com/vahidAK/PatMat</a>.
It was converted to browser coordinates without any other change, and all 192
regions are shown. The processing steps are documented in the
<a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/imprinting.txt" target="_blank">imprinting makeDoc</a>
and the script is in
<a href="https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/scripts/imprinting" target="_blank">makeDb/scripts/imprinting</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>akbariIdmr</i>.
</p>
<p>
For automated download and analysis, the genome annotation is stored in a
bigBed file that can be downloaded from
<a href="http://hgdownload.soe.ucsc.edu/gbdb/hg38/imprinting/akbari2023/" target="_blank">our download server</a>.
The file for this track is called <tt>akbariIdmr.bb</tt>. Individual regions or
the whole genome annotation can be obtained using our tool
<tt>bigBedToBed</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 features within a given range, e.g.
<tt>bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg38/imprinting/akbari2023/akbariIdmr.bb -chrom=chr11 -start=1900000 -end=2800000 stdout</tt>
</p>
<p>
The original region list can be downloaded from the
<a href="https://github.com/vahidAK/PatMat" target="_blank">PatMat repository</a>
or from the supplementary material of the paper.
</p>
<h2>Credits</h2>
<p>
Thanks to Vahid Akbari and colleagues at Canada's Michael Smith Genome Sciences
Centre and the University of British Columbia for compiling and publishing the
region list.
</p>
<h2>References</h2>
<p>
Akbari V, Hanlon VCT, O'Neill K, Lefebvre L, Schrader KA, Lansdorp PM, Jones SJM.
<a href="https://www.ncbi.nlm.nih.gov/pubmed/36777186" target="_blank">
Parent-of-origin detection and chromosome-scale haplotyping using long-read DNA methylation
sequencing and Strand-seq</a>.
<em>Cell Genom</em>. 2023 Jan 11;3(1):100233.
PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/36777186" target="_blank">36777186</a>; PMC: <a
href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9903809/" target="_blank">PMC9903809</a>
</p>
<p>
Akbari V, Garant JM, O'Neill K, Pandoh P, Moore R, Marra MA, Hirst M, Jones SJM.
<a href="https://www.ncbi.nlm.nih.gov/pubmed/35787786" target="_blank">
Genome-wide detection of imprinted differentially methylated regions using nanopore sequencing</a>.
<em>Elife</em>. 2022 Jul 5;11.
PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/35787786" target="_blank">35787786</a>; PMC: <a
href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9255983/" target="_blank">PMC9255983</a>
</p>
<p>
Zink F, Magnusdottir DN, Magnusson OT, Walker NJ, Morris TJ, Sigurdsson A, Halldorsson GH,
Gudjonsson SA, Melsted P, Ingimundardottir H <em>et al</em>.
<a href="https://www.ncbi.nlm.nih.gov/pubmed/30349119" target="_blank">
Insights into imprinting from parent-of-origin phased methylomes and transcriptomes</a>.
<em>Nat Genet</em>. 2018 Nov;50(11):1542-1552.
PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/30349119" target="_blank">30349119</a>
</p>
<p>
Hernandez Mora JR, Tayama C, Sánchez-Delgado M, Monteagudo-Sánchez A, Hata K, Ogata T, Medrano J,
Poo-Llanillo ME, Simón C, Moran S <em>et al</em>.
<a href="https://www.tandfonline.com/doi/10.2217/epi-2017-0172?url_ver=Z39.88-2003&rfr_id=ori:ri
d:crossref.org&rfr_dat=cr_pub%20%200pubmed" target="_blank">
Characterization of parent-of-origin methylation using the Illumina Infinium MethylationEPIC array
platform</a>.
<em>Epigenomics</em>. 2018 Jul;10(7):941-954.
PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/29962238" target="_blank">29962238</a>
</p>
<p>
Joshi RS, Garg P, Zaitlen N, Lappalainen T, Watson CT, Azam N, Ho D, Li X, Antonarakis SE, Brunner
HG <em>et al</em>.
<a href="https://www.ncbi.nlm.nih.gov/pubmed/27569549" target="_blank">
DNA Methylation Profiling of Uniparental Disomy Subjects Provides a Map of Parental Epigenetic Bias
in the Human Genome</a>.
<em>Am J Hum Genet</em>. 2016 Sep 1;99(3):555-566.
PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/27569549" target="_blank">27569549</a>; PMC: <a
href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5011056/" target="_blank">PMC5011056</a>
</p>
<p>
Court F, Tayama C, Romanelli V, Martin-Trujillo A, Iglesias-Platas I, Okamura K, Sugahara N, Simón
C, Moore H, Harness JV <em>et al</em>.
<a href="https://www.ncbi.nlm.nih.gov/pubmed/24402520" target="_blank">
Genome-wide parent-of-origin DNA methylation analysis reveals the intricacies of human imprinting
and suggests a germline methylation-independent mechanism of establishment</a>.
<em>Genome Res</em>. 2014 Apr;24(4):554-69.
PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/24402520" target="_blank">24402520</a>; PMC: <a
href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3975056/" target="_blank">PMC3975056</a>
</p>