{"status":"OK","data":{"id":55606,"identifier":"DVN/PTXNNB","persistentUrl":"https://doi.org/10.7910/DVN/PTXNNB","protocol":"doi","authority":"10.7910","separator":"/","publisher":"Harvard Dataverse","publicationDate":"2010-11-18","storageIdentifier":"s3://1902.1/15333","effectiveDatasetFileCountLimit":1000,"datasetFileUploadsAvailable":998,"datasetType":"dataset","locks":[],"latestVersion":{"id":54347,"datasetId":55606,"datasetPersistentId":"doi:10.7910/DVN/PTXNNB","datasetType":"dataset","storageIdentifier":"s3://1902.1/15333","versionNumber":1,"internalVersionNumber":1,"versionMinorNumber":0,"versionState":"RELEASED","latestVersionPublishingState":"RELEASED","deaccessionNote":"","deaccessionLink":"","productionDate":"2010-09-07","lastUpdateTime":"2010-11-18T19:11:13Z","releaseTime":"2010-11-18T00:00:00Z","createTime":"2010-11-18T19:09:45Z","alternativePersistentId":"hdl:1902.1/15333","publicationDate":"2010-11-18","citationDate":"2010-11-18","effectiveDatasetFileCountLimit":1000,"datasetFileUploadsAvailable":998,"license":{"name":"CC0 1.0","uri":"http://creativecommons.org/publicdomain/zero/1.0","iconUri":"https://licensebuttons.net/p/zero/1.0/88x31.png","rightsIdentifier":"CC0-1.0","rightsIdentifierScheme":"SPDX","schemeUri":"https://spdx.org/licenses/","languageCode":"en"},"fileAccessRequest":false,"metadataBlocks":{"citation":{"displayName":"Citation Metadata","name":"citation","fields":[{"typeName":"title","multiple":false,"typeClass":"primitive","value":"Increased Power for the Analysis of Label-Free LC-MS/MS Proteomic Data by Combining Spectral Counts and Peptide Peak Attributes"},{"typeName":"author","multiple":true,"typeClass":"compound","value":[{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Lee Dicker"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Harvard School of Public Health"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Xihong Lin"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Harvard School of Public Health"}},{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Alexander Ivanov"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"Harvard School of Public Health"}}]},{"typeName":"datasetContact","multiple":true,"typeClass":"compound","value":[{"datasetContactEmail":{"typeName":"datasetContactEmail","multiple":false,"typeClass":"primitive","value":"N/A"}}]},{"typeName":"dsDescription","multiple":true,"typeClass":"compound","value":[{"dsDescriptionValue":{"typeName":"dsDescriptionValue","multiple":false,"typeClass":"primitive","value":"Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics provides a wealth of information about proteins present in biological samples.  In bottom-up LC-MS/MS-based proteomics, proteins are enzymatically digested into peptides prior to query by LC-MS/MS.  Thus, the information directly available from the LC-MS/MS data is at the peptide level.  If a protein-level analysis is desired, the peptide-level information must be tolled up into protein-level information.  We propose a principal components analysis-based statistical method, ProPCA, for efficiently estimating relative protein abundance from bottom-up label-free LC-MS/MS data, which incorporates both spectral count information and LC-MS peptide ion peak attributes, such as peak area, volume or height.  ProPCA may be used effectively with a variety of quantification platforms and is easily implemented.  We show that ProPCA outperforms existing quantitative methods for peptide-protein roll up, including special counting methods and other methods for combining LC-MS peptide peak attributes.  The performance of ProPCA is validated using a dataset derived from the LC-MS/MS analysis of a mixture of protein standards (the UPS2 proteomic dynamic range standard introduced by the ABRF Proteomics Standards Research Group, 2006).  Finally, we apply ProPCA to a comparative LC-MS/MS analysis of digested total cell lysates prepared for LC-MS/MS analysis by alternative lysis methods and show that ProPCA identifies more differently abundant proteins than competing methods."}}]},{"typeName":"topicClassification","multiple":true,"typeClass":"compound","value":[{"topicClassValue":{"typeName":"topicClassValue","multiple":false,"typeClass":"primitive","value":"Statistical Genetics, Genomics, and Omics"}}]},{"typeName":"productionDate","multiple":false,"typeClass":"primitive","value":"2010-09-07"},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2010-11-18"}]}},"files":[{"description":"","label":"mcp.M110.002774-1.pdf","restricted":false,"version":1,"datasetVersionId":54347,"dataFile":{"id":1820491,"persistentId":"doi:10.7910/DVN/PTXNNB/BQVKW2","pidURL":"https://doi.org/10.7910/DVN/PTXNNB/BQVKW2","filename":"mcp.M110.002774-1.pdf","contentType":"application/pdf","friendlyType":"Adobe PDF","filesize":1264306,"description":"","storageIdentifier":"s3://dvn-cloud:62151","rootDataFileId":-1,"md5":"064174e488c263f4aab14c628063e116","checksum":{"type":"MD5","value":"064174e488c263f4aab14c628063e116"},"tabularData":false,"creationDate":"2010-11-18","publicationDate":"2010-11-17","lastUpdateTime":"2010-11-18T19:11:13Z","fileAccessRequest":false}},{"description":"","label":"mcp.M110.002774.full.pdf","restricted":false,"version":1,"datasetVersionId":54347,"dataFile":{"id":1820490,"persistentId":"doi:10.7910/DVN/PTXNNB/4YYOBI","pidURL":"https://doi.org/10.7910/DVN/PTXNNB/4YYOBI","filename":"mcp.M110.002774.full.pdf","contentType":"application/pdf","friendlyType":"Adobe PDF","filesize":525527,"description":"","storageIdentifier":"s3://dvn-cloud:62150","rootDataFileId":-1,"md5":"9f165a35b1b47d5f20d34b49fdd2b107","checksum":{"type":"MD5","value":"9f165a35b1b47d5f20d34b49fdd2b107"},"tabularData":false,"creationDate":"2010-11-18","publicationDate":"2010-11-17","lastUpdateTime":"2010-11-18T19:11:13Z","fileAccessRequest":false}}]}}}