e461209cf1fd3758d63641915cd91ca9c8ab3020 lrnassar Thu Sep 24 17:00:10 2026 -0700 Remove tool output accidentally left in the mei description page, per CR. refs #37524 getTrackReferences writes its diagnostics to stdout rather than stderr, so six "Failed to fetch complete links from NCBI" lines ended up in the References section of mei.html and rendered as visible text on the track description page. NCBI is still not answering, so rather than rerun the tool the references are now assembled from the citation blocks already present on the six subtrack pages. That also restores the publisher links for every paper, which the failed lookups had degraded to bare PubMed URLs. Also make the INFO SEQ guard in meiHgsvc3CsvToBed.py require a usable string, so an empty SEQ= value would fall back to the ALT-derived sequence instead of silently producing an empty one. No record in either callset carries an empty SEQ today and the rebuilt output is byte-identical. diff --git src/hg/makeDb/trackDb/human/mei.html src/hg/makeDb/trackDb/human/mei.html index ee66fe4ea7e..170960355d6 100644 --- src/hg/makeDb/trackDb/human/mei.html +++ src/hg/makeDb/trackDb/human/mei.html @@ -90,89 +90,83 @@ <p> Filters available on the subtrack configuration page allow restricting the displayed items by element class, insertion length, allele frequency, number of carrier samples, the number of MEI callers that supported the call, validation by L1ME-AID or PALMER, and overlap with reference segmental duplications and tandem repeats. </p> <h2>Data Access</h2> <p> Each subtrack has its own description page with details on file location, the autoSql schema, citation and download instructions. </p> <h2>References</h2> -Failed to fetch complete links from NCBI after 10 tries. Try again later or just use the PubMed paper link. -Failed to fetch complete links from NCBI after 10 tries. Try again later or just use the PubMed paper link. -Failed to fetch complete links from NCBI after 10 tries. Try again later or just use the PubMed paper link. -Failed to fetch complete links from NCBI after 10 tries. Try again later or just use the PubMed paper link. -Failed to fetch complete links from NCBI after 10 tries. Try again later or just use the PubMed paper link. -Failed to fetch complete links from NCBI after 10 tries. Try again later or just use the PubMed paper link. - <p> Ameur A, Dahlberg J, Olason P, Vezzi F, Karlsson R, Martin M, Viklund J, Kähäri AK, Lundin P, Che H <em>et al</em>. -<a href="https://www.ncbi.nlm.nih.gov/pubmed/28832569" target="_blank"> +<a href="https://doi.org/10.1038/ejhg.2017.130" target="_blank"> SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population</a>. <em>Eur J Hum Genet</em>. 2017 Nov;25(11):1253-1260. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/28832569" target="_blank">28832569</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5765326/" target="_blank">PMC5765326</a> </p> <p> Byrska-Bishop M, Evani US, Zhao X, Basile AO, Abel HJ, Regier AA, Corvelo A, Clarke WE, Musunuri R, Nagulapalli K <em>et al</em>. -<a href="https://www.ncbi.nlm.nih.gov/pubmed/36055201" target="_blank"> +<a href="https://linkinghub.elsevier.com/retrieve/pii/S0092-8674(22)00991-6" target="_blank"> High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios</a>. <em>Cell</em>. 2022 Sep 1;185(18):3426-3440.e19. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/36055201" target="_blank">36055201</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9439720/" target="_blank">PMC9439720</a> </p> <p> Gardner EJ, Lam VK, Harris DN, Chuang NT, Scott EC, Pittard WS, Mills RE, 1000 Genomes Project Consortium, Devine SE. -<a href="https://www.ncbi.nlm.nih.gov/pubmed/28855259" target="_blank"> +<a href="http://genome.cshlp.org/lookup/pmidlookup?view=long&pmid=28855259" target="_blank"> The Mobile Element Locator Tool (MELT): population-scale mobile element discovery and biology</a>. <em>Genome Res</em>. 2017 Nov;27(11):1916-1929. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/28855259" target="_blank">28855259</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5668948/" target="_blank">PMC5668948</a> </p> <p> Logsdon GA, Ebert P, Audano PA, Loftus M, Porubsky D, Ebler J, Yilmaz F, Hallast P, Prodanov T, Yoo D <em>et al</em>. -<a href="https://www.ncbi.nlm.nih.gov/pubmed/40702183" target="_blank"> +<a href="https://doi.org/10.1038/s41586-025-09140-6" target="_blank"> Complex genetic variation in nearly complete human genomes</a>. <em>Nature</em>. 2025 Aug;644(8076):430-441. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/40702183" target="_blank">40702183</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12350169/" target="_blank">PMC12350169</a> </p> <p> Mir AA, Philippe C, Cristofari G. -<a href="https://www.ncbi.nlm.nih.gov/pubmed/25352549" target="_blank"> +<a href="https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gku1043" target="_blank"> euL1db: the European database of L1HS retrotransposon insertions in humans</a>. <em>Nucleic Acids Res</em>. 2015 Jan;43(Database issue):D43-7. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/25352549" target="_blank">25352549</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4383891/" target="_blank">PMC4383891</a> </p> <p> Niu Y, Teng X, Zhou H, Shi Y, Li Y, Tang Y, Zhang P, Luo H, Kang Q, Xu T <em>et al</em>. -<a href="https://www.ncbi.nlm.nih.gov/pubmed/35212372" target="_blank"> +<a href="https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkac128" target="_blank"> Characterizing mobile element insertions in 5675 genomes</a>. <em>Nucleic Acids Res</em>. 2022 Mar 21;50(5):2493-2508. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/35212372" target="_blank">35212372</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8934628/" target="_blank">PMC8934628</a> </p> + <p> Xu X, Huang Y, Wang X, Cheng J, Yuan H, Bu F. <a href="https://doi.org/10.1101/2023.03.07.531451" target="_blank"> Identification of mobile element insertion from whole genome sequencing data using deep neural network model</a>. <em>bioRxiv</em>. 2023 March 8. doi:10.1101/2023.03.07.531451. </p>