32048e16a50722894cf28d9b7b4b050302e38c75 markd Wed Sep 30 17:54:58 2026 -0700 Spell the acronym PCLAI, not pcLAI. refs #35415 The authors write it PCLAI throughout: the upstream README at AI-sandbox/hprc-pclai uses PCLAI 18 times and pcLAI never, under the title "Point Cloud Local Ancestry Inference (PCLAI)". We had pcLAI in 517 places, across the track labels, both description pages, the makedocs, the build scripts and the autoSql. hprcPclai.ra holds 467 of those, in shortLabel, longLabel, dataVersion and comments. It is generated, so the fix went into hprcPclaiMakeTrackDb.py and the file was rebuilt; every line of the resulting diff differs only by the rename. Track names, file names and the lowercase pclai in URLs and data file names are untouched. None of them contained the string pcLAI, and renaming the tracks would break saved sessions for no user-visible gain. diff --git src/hg/makeDb/trackDb/human/hg38/hprcPclai.html src/hg/makeDb/trackDb/human/hg38/hprcPclai.html index 081f32cdf58..f4489acda79 100644 --- src/hg/makeDb/trackDb/human/hg38/hprcPclai.html +++ src/hg/makeDb/trackDb/human/hg38/hprcPclai.html @@ -1,146 +1,146 @@ <h2>Description</h2> <p> Every person's genome is a mosaic inherited from ancestors of different populations, and "local ancestry" describes, region by region along a chromosome, -where a stretch of DNA came from. Point cloud local ancestry inference (pcLAI) +where a stretch of DNA came from. Point cloud local ancestry inference (PCLAI) does this without picking one population label per region: it places each region at a point in a continuous coordinate space, so ancestry that sits between two reference populations stays visible as an intermediate position instead of being rounded to the nearest label. </p> <p> -This track shows pcLAI for Human Pangenome Reference Consortium (HPRC) Release 2, +This track shows PCLAI for Human Pangenome Reference Consortium (HPRC) Release 2, projected from each assembly onto GRCh38: both haplotypes of 231 samples, plus CHM13, so 463 subtracks in all. Each haplotype is divided into windows of 1000 SNPs, which works out to roughly a hundred thousand bases, about 26,000 windows per haplotype and 11.9 million in total. Only the autosomes are covered. </p> <h2>Display Conventions</h2> <p> Each item is one genomic window. Items carry no visible label. Holding the mouse over an item shows the haplotype, the window identifier, the position of the -window in the principal-component space that pcLAI uses to describe ancestry, the +window in the principal-component space that PCLAI uses to describe ancestry, the ancestry the window is assigned to if the continuous coordinate is discretized, and a confidence score; the same values are on the details page, together with a scatterplot showing where the window sits relative to the reference haplotypes that define the space. </p> <p> The item color is derived from the principal-component position, so windows of similar inferred ancestry get similar colors and a run of shared ancestry appears as a block of consistent color. Because the color is continuous rather than a set of population labels, it is read by comparing regions with each other rather than against a fixed legend. Neighboring windows inside one block differ by only one or two color steps, and those small differences are not meaningful: the feature to read is the block, not the window. </p> <p> Two consequences are worth knowing before concluding that a display looks wrong. First, a haplotype with a single ancestry throughout gives one uniform color across every chromosome, which is the correct result for that sample rather than a rendering problem; 48 of the 463 haplotypes are like this. Second, where a haplotype does carry several ancestries the blocks are tens of megabases long, so a view of only a few megabases usually falls inside one block and also looks uniform. Zooming out to a whole chromosome is what makes the block structure visible. </p> <p> The track opens with seven haplotypes turned on. Five of them were picked because their ancestry is visibly mixed: NA19682 (both haplotypes), NA19776, HG01496 and HG01150 each carry a second ancestry over more than a quarter of the genome. The other two, HG002 and CHM13, are there as familiar reference points and are close to uniform. The remaining haplotypes can be turned on from the sample-by-haplotype matrix on the track configuration page. </p> <p> Dense mode is the mode to use. It draws one row per haplotype, and because the items carry no label nothing is lost by collapsing them: a window is still clicked or moused over for its values. Pack mode adds nothing here and costs a lot of vertical space, since the windows abut and pack puts each one on a different row from its neighbour. </p> <h2>Methods</h2> <p> Conventional local ancestry inference gives every segment of a genome one of a -fixed set of population labels. pcLAI instead places each segment at a point in a +fixed set of population labels. PCLAI instead places each segment at a point in a continuous coordinate space, so a genome becomes a cloud of points, one per window. The coordinate space can be any continuous description of ancestry; here it is the first two principal components of a reference PCA embedding built from 3122 1000 Genomes haplotypes of 21 populations of known origin. Each haplotype was split into windows of 1000 SNPs and a coordinate predicted for each, together with a confidence score; windows of very low confidence were dropped before the BED files were published, which together with the projection onto GRCh38 is why the windows do not tile a chromosome without gaps (for NA19682 haplotype 1, 2.73 of the 2.88 Gb of autosome is covered, with about 65 Mb of internal gaps). The files also carry a discretized version of each prediction, written as the PCA centroid of the ancestry cluster the window falls in, and across all 463 haplotypes that takes only four values. See the reference below for the method, and the -<a href="https://github.com/AI-sandbox/hprc-pclai" target="_blank">pcLAI repository</a> +<a href="https://github.com/AI-sandbox/hprc-pclai" target="_blank">PCLAI repository</a> for the code and the reference panel table. </p> <p> The annotation files were obtained from the HPRC Release 2 data collection on the public <tt>s3://human-pangenomics</tt> bucket, indexed at <a href="https://github.com/human-pangenomics/hprc_intermediate_assembly/tree/main/data_tables/annotation/pclai" target="_blank">the hprc_intermediate_assembly data tables</a>; this track uses the GRCh38-coordinate index, <tt>pclai_v1.1_grch38_coord_local_hprc_r2.index.csv</tt>. Each per-haplotype BED file was converted to a UCSC bigBed file, with the haplotype, the window identifier and the window's own principal-component coordinate split out of the source item name into their own fields, and the source's centroid column named. All 11,936,603 windows in the source files are carried through to the bigBeds; none were dropped. In 54,811 of them (0.46%) the source <tt>thickStart</tt> is one base before <tt>chromStart</tt> and so -outside the item, which is invalid BED and also departs from the format the pcLAI +outside the item, which is invalid BED and also departs from the format the PCLAI authors document; since <tt>thickStart</tt> and <tt>thickEnd</tt> carry no information for this annotation they were set to the item bounds rather than dropping those windows. The steps are described in the <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/hprcPclai.txt" target="_blank">makeDoc</a> and the build scripts are in the <a href="https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/scripts/hprcPclai" 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" target="_blank">API</a>, track=<i>hprcPclai</i>. </p> <p> For automated download and analysis, the annotation is stored in one bigBed file per haplotype, which can be downloaded from <a href="http://hgdownload.soe.ucsc.edu/gbdb/hg38/hprcPclai/" target="_blank">our download server</a>. The files are called <tt>SAMPLE.HAPLOTYPE.bb</tt>, for example <tt>NA19682.1.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" target="_blank">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/hprcPclai/NA19682.1.bb -chrom=chr21 -start=0 -end=100000000 stdout</tt> </p> <p> The original annotation source data can be downloaded from the HPRC S3 bucket linked above. </p> <h2>Credits</h2> <p> Annotations were generated by the Human Pangenome Reference Consortium. Thanks to -the HPRC production team and to the pcLAI authors for making these data available. +the HPRC production team and to the PCLAI authors for making these data available. </p> <h2>References</h2> <p> Geleta M, Mas Montserrat D, Ioannidis NM, Ioannidis AG. <a href="https://doi.org/10.64898/2026.03.23.713813" target="_blank"> Point cloud local ancestry inference (PCLAI): continuous coordinate-based ancestry along the genome</a>. <em>bioRxiv</em>. 2026 Mar 25. doi: <a href="https://doi.org/10.64898/2026.03.23.713813" target="_blank">10.64898/2026.03.23.713813</a> </p>