<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><submitter>Tsantilas KA</submitter><funding>NIA NIH HHS</funding><funding>NIGMS NIH HHS</funding><pubmed_abstract>A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow from planning to analysis. We share vignettes applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at protein and peptide-level allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to veri</pubmed_abstract><journal>bioRxiv : the preprint server for biology</journal><pagination>2024.04.12.589318</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11030400</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>A framework for quality control in quantitative proteomics.</pubmed_title><pmcid>PMC11030400</pmcid><funding_grant_id>P30 AG013280</funding_grant_id><funding_grant_id>F31 AG069420</funding_grant_id><funding_grant_id>T32 AG066574</funding_grant_id><funding_grant_id>RF1 AG053959</funding_grant_id><funding_grant_id>U19 AG065156</funding_grant_id><funding_grant_id>R24 GM141156</funding_grant_id><pubmed_authors>Johnson RS</pubmed_authors><pubmed_authors>Huang E</pubmed_authors><pubmed_authors>Hoofnagle AN</pubmed_authors><pubmed_authors>Park J</pubmed_authors><pubmed_authors>MacCoss MJ</pubmed_authors><pubmed_authors>Riffle M</pubmed_authors><pubmed_authors>Bereman MS</pubmed_authors><pubmed_authors>MacLean BX</pubmed_authors><pubmed_authors>Tsantilas KA</pubmed_authors><pubmed_authors>Plubell DL</pubmed_authors><pubmed_authors>Sharma V</pubmed_authors><pubmed_authors>Merrihew GE</pubmed_authors><pubmed_authors>Eckels J</pubmed_authors><pubmed_authors>Canterbury JD</pubmed_authors><pubmed_authors>Robbins JE</pubmed_authors><pubmed_authors>Wu CC</pubmed_authors><pubmed_authors>Spencer SE</pubmed_authors></additional><is_claimable>false</is_claimable><name>A framework for quality control in quantitative proteomics.</name><description>A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow from planning to analysis. We share vignettes applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at protein and peptide-level allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to veri</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Aug</publication><modification>2026-04-08T18:31:51.295Z</modification><creation>2026-04-08T09:40:41.859Z</creation></dates><accession>S-EPMC11030400</accession><cross_references><pubmed>38645098</pubmed><doi>10.1101/2024.04.12.589318</doi></cross_references></HashMap>