O-Pair Search with MetaMorpheus for O-glycopeptide characterization
We report O-Pair Search, an approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides via an ion-indexed open modification search and localizes O-glycosites using graph theory and probabil...
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| Veröffentlicht in: | Nature methods 2020-11, Vol.17 (11), p.1133-1138 |
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| container_title | Nature methods |
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| creator | Lu, Lei Riley, Nicholas M. Shortreed, Michael R. Bertozzi, Carolyn R. Smith, Lloyd M. |
| description | We report O-Pair Search, an approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides via an ion-indexed open modification search and localizes O-glycosites using graph theory and probability-based localization. O-Pair Search reduces search times more than 2,000-fold compared to current O-glycopeptide processing software, while defining O-glycosite localization confidence levels and generating more O-glycopeptide identifications. Beyond the mucin-type O-glycopeptides discussed here, O-Pair Search also accepts user-defined glycan databases, making it compatible with many types of O-glycosylation. O-Pair Search is freely available within the open-source MetaMorpheus platform at
https://github.com/smith-chem-wisc/MetaMorpheus
.
O-Pair search identifies O-glycopeptides and localizes O-glycosites using a fragment-ion-indexed open modification search combined with a graph-based approach. It also introduces a classification scheme to unify data reporting for glycoproteomics. |
| doi_str_mv | 10.1038/s41592-020-00985-5 |
| format | Article |
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https://github.com/smith-chem-wisc/MetaMorpheus
.
O-Pair search identifies O-glycopeptides and localizes O-glycosites using a fragment-ion-indexed open modification search combined with a graph-based approach. It also introduces a classification scheme to unify data reporting for glycoproteomics.</description><identifier>ISSN: 1548-7091</identifier><identifier>EISSN: 1548-7105</identifier><identifier>DOI: 10.1038/s41592-020-00985-5</identifier><identifier>PMID: 33106676</identifier><language>eng</language><publisher>New York: Nature Publishing Group US</publisher><subject>631/114/2784 ; 631/1647/2067 ; 631/1647/296 ; 631/1647/794 ; 631/80/458/1524 ; Antibiotics ; Bioinformatics ; Biological Microscopy ; Biological Techniques ; Biomedical and Life Sciences ; Biomedical Engineering/Biotechnology ; Confidence intervals ; Databases, Protein ; Glycan ; Glycopeptides ; Glycopeptides - analysis ; Glycopeptides - chemistry ; Glycoproteins ; Glycosylation ; Graph theory ; Health aspects ; Identification and classification ; Life Sciences ; Localization ; Methods ; Mucin ; Peptides ; Probability ; Proteomics ; Proteomics - instrumentation ; Proteomics - methods ; Public software ; Searching ; Software ; Source code ; Statistical analysis ; Tandem Mass Spectrometry ; Workflow</subject><ispartof>Nature methods, 2020-11, Vol.17 (11), p.1133-1138</ispartof><rights>The Author(s), under exclusive licence to Springer Nature America, Inc. 2020</rights><rights>COPYRIGHT 2020 Nature Publishing Group</rights><rights>The Author(s), under exclusive licence to Springer Nature America, Inc. 2020.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c541t-d92c8aeb1824dc78f9b947467e9805d7f1fca1770a07a4392812785e59a8fc273</citedby><cites>FETCH-LOGICAL-c541t-d92c8aeb1824dc78f9b947467e9805d7f1fca1770a07a4392812785e59a8fc273</cites><orcidid>0000-0001-7097-1505 ; 0000-0003-4482-2754 ; 0000-0002-6652-8639</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/s41592-020-00985-5$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/s41592-020-00985-5$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33106676$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lu, Lei</creatorcontrib><creatorcontrib>Riley, Nicholas M.</creatorcontrib><creatorcontrib>Shortreed, Michael R.</creatorcontrib><creatorcontrib>Bertozzi, Carolyn R.</creatorcontrib><creatorcontrib>Smith, Lloyd M.</creatorcontrib><title>O-Pair Search with MetaMorpheus for O-glycopeptide characterization</title><title>Nature methods</title><addtitle>Nat Methods</addtitle><addtitle>Nat Methods</addtitle><description>We report O-Pair Search, an approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides via an ion-indexed open modification search and localizes O-glycosites using graph theory and probability-based localization. O-Pair Search reduces search times more than 2,000-fold compared to current O-glycopeptide processing software, while defining O-glycosite localization confidence levels and generating more O-glycopeptide identifications. Beyond the mucin-type O-glycopeptides discussed here, O-Pair Search also accepts user-defined glycan databases, making it compatible with many types of O-glycosylation. O-Pair Search is freely available within the open-source MetaMorpheus platform at
https://github.com/smith-chem-wisc/MetaMorpheus
.
O-Pair search identifies O-glycopeptides and localizes O-glycosites using a fragment-ion-indexed open modification search combined with a graph-based approach. 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Nature methods</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lu, Lei</au><au>Riley, Nicholas M.</au><au>Shortreed, Michael R.</au><au>Bertozzi, Carolyn R.</au><au>Smith, Lloyd M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>O-Pair Search with MetaMorpheus for O-glycopeptide characterization</atitle><jtitle>Nature methods</jtitle><stitle>Nat Methods</stitle><addtitle>Nat Methods</addtitle><date>2020-11-01</date><risdate>2020</risdate><volume>17</volume><issue>11</issue><spage>1133</spage><epage>1138</epage><pages>1133-1138</pages><issn>1548-7091</issn><eissn>1548-7105</eissn><abstract>We report O-Pair Search, an approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides via an ion-indexed open modification search and localizes O-glycosites using graph theory and probability-based localization. O-Pair Search reduces search times more than 2,000-fold compared to current O-glycopeptide processing software, while defining O-glycosite localization confidence levels and generating more O-glycopeptide identifications. Beyond the mucin-type O-glycopeptides discussed here, O-Pair Search also accepts user-defined glycan databases, making it compatible with many types of O-glycosylation. O-Pair Search is freely available within the open-source MetaMorpheus platform at
https://github.com/smith-chem-wisc/MetaMorpheus
.
O-Pair search identifies O-glycopeptides and localizes O-glycosites using a fragment-ion-indexed open modification search combined with a graph-based approach. It also introduces a classification scheme to unify data reporting for glycoproteomics.</abstract><cop>New York</cop><pub>Nature Publishing Group US</pub><pmid>33106676</pmid><doi>10.1038/s41592-020-00985-5</doi><tpages>6</tpages><orcidid>https://orcid.org/0000-0001-7097-1505</orcidid><orcidid>https://orcid.org/0000-0003-4482-2754</orcidid><orcidid>https://orcid.org/0000-0002-6652-8639</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | 631/114/2784 631/1647/2067 631/1647/296 631/1647/794 631/80/458/1524 Antibiotics Bioinformatics Biological Microscopy Biological Techniques Biomedical and Life Sciences Biomedical Engineering/Biotechnology Confidence intervals Databases, Protein Glycan Glycopeptides Glycopeptides - analysis Glycopeptides - chemistry Glycoproteins Glycosylation Graph theory Health aspects Identification and classification Life Sciences Localization Methods Mucin Peptides Probability Proteomics Proteomics - instrumentation Proteomics - methods Public software Searching Software Source code Statistical analysis Tandem Mass Spectrometry Workflow |
| title | O-Pair Search with MetaMorpheus for O-glycopeptide characterization |
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