{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T10:59:06Z","timestamp":1788951546927,"version":"build-2803163510"},"reference-count":8,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2021,12,14]],"date-time":"2021-12-14T00:00:00Z","timestamp":1639440000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Swedish Cancer Society [CAN","award":["2017\/685"],"award-info":[{"award-number":["2017\/685"]}]},{"name":"Swedish Cancer Society [CAN","award":["CAN 2020\/1269"],"award-info":[{"award-number":["CAN 2020\/1269"]}]},{"DOI":"10.13039\/100007436","name":"Erling-Persson Family Foundation","doi-asserted-by":"publisher","award":["12\/12-2017"],"award-info":[{"award-number":["12\/12-2017"]}],"id":[{"id":"10.13039\/100007436","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007436","name":"Erling-Persson Family Foundation","doi-asserted-by":"publisher","award":["22\/9-2020"],"award-info":[{"award-number":["22\/9-2020"]}],"id":[{"id":"10.13039\/100007436","id-type":"DOI","asserted-by":"publisher"}]},{"name":"DART and Rescuer EU-projects"},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32100505"],"award-info":[{"award-number":["32100505"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007162","name":"Guangdong Science and Technology Department","doi-asserted-by":"publisher","award":["2020B1212060018"],"award-info":[{"award-number":["2020B1212060018"]}],"id":[{"id":"10.13039\/501100007162","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007162","name":"Guangdong Science and Technology Department","doi-asserted-by":"publisher","award":["2020B1212030004"],"award-info":[{"award-number":["2020B1212030004"]}],"id":[{"id":"10.13039\/501100007162","id-type":"DOI","asserted-by":"publisher"}]},{"name":"German Ministry of Research and Education","award":["031A535A"],"award-info":[{"award-number":["031A535A"]}]},{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["208391\/Z\/17\/Z"],"award-info":[{"award-number":["208391\/Z\/17\/Z"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,2,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>We have implemented the pypgatk package and the pgdb workflow to create proteogenomics databases based on ENSEMBL resources. The tools allow the generation of protein sequences from novel protein-coding transcripts by performing a three-frame translation of pseudogenes, lncRNAs and other non-canonical transcripts, such as those produced by alternative splicing events. It also includes exonic out-of-frame translation from otherwise canonical protein-coding mRNAs. Moreover, the tool enables the generation of variant protein sequences from multiple sources of genomic variants including COSMIC, cBioportal, gnomAD and mutations detected from sequencing of patient samples. pypgatk and pgdb provide multiple functionalities for database handling including optimized target\/decoy generation by the algorithm DecoyPyrat. Finally, we have reanalyzed six public datasets in PRIDE by generating cell-type specific databases for 65 cell lines using the pypgatk and pgdb workflow, revealing a wealth of non-canonical or cryptic peptides amounting to &amp;gt;5% of the total number of peptides identified.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The software is freely available. pypgatk: https:\/\/github.com\/bigbio\/py-pgatk\/ and pgdb: https:\/\/nf-co.re\/pgdb.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab838","type":"journal-article","created":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T07:27:24Z","timestamp":1639121244000},"page":"1470-1472","source":"Crossref","is-referenced-by-count":26,"title":["Generation of ENSEMBL-based proteogenomics databases boosts the identification of non-canonical peptides"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3971-2462","authenticated-orcid":false,"given":"Husen M","family":"Umer","sequence":"first","affiliation":[{"name":"Department of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet , Stockholm 17165, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enrique","family":"Audain","sequence":"additional","affiliation":[{"name":"Department of Congenital Heart Disease and Pediatric Cardiology, Universit\u00e4tsklinikum Schleswig-Holstein Kiel , Kiel 24105, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yafeng","family":"Zhu","sequence":"additional","affiliation":[{"name":"Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-sen University , Guangzhou 510120, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julianus","family":"Pfeuffer","sequence":"additional","affiliation":[{"name":"Algorithmic Bioinformatics, Freie Universit\u00e4t Berlin , Berlin 14195, Germany"},{"name":"Visualization and Data Analysis, Zuse Institute Berlin , Berlin 14195, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timo","family":"Sachsenberg","sequence":"additional","affiliation":[{"name":"Institute for Bioinformatics and Medical Informatics, University of T\u00fcbingen , 72076 T\u00fcbingen , Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Janne","family":"Lehti\u00f6","sequence":"additional","affiliation":[{"name":"Department of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet , Stockholm 17165, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui M","family":"Branca","sequence":"additional","affiliation":[{"name":"Department of Oncology-Pathology, Science for Life Laboratory, Karolinska Institutet , Stockholm 17165, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6579-6941","authenticated-orcid":false,"given":"Yasset","family":"Perez-Riverol","sequence":"additional","affiliation":[{"name":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus , Hinxton, Cambridge CB10 1SD, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,12,14]]},"reference":[{"key":"2023020108561199900_btab838-B1","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1038\/nmeth.2732","article-title":"HiRIEF LC-MS enables deep proteome coverage and unbiased proteogenomics","volume":"11","author":"Branca","year":"2014","journal-title":"Nat. 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