Accounting for spot matching uncertainty in the analysis of proteomics data from two-dimensional gel electrophoresis

dc.contributor.author Melnykov, Volodymyr
dc.contributor.author Maitra, Ranjan
dc.contributor.author Nettleton, Dan
dc.contributor.author Nettleton, Dan
dc.contributor.department Statistics
dc.date 2018-02-17T18:36:20.000
dc.date.accessioned 2020-07-02T06:58:02Z
dc.date.available 2020-07-02T06:58:02Z
dc.date.copyright Sat Jan 01 00:00:00 UTC 2011
dc.date.issued 2011-05-01
dc.description.abstract <p>Two-dimensional gel electrophoresis is a biochemical technique that combines isoelectric focusing and SDS-polyacrylamide gel technology to achieve simultaneous separation of protein mixtures on the basis of isoelectric point and molecular weight. Upon staining, each protein on a gel can be characterized by an intensity measurement that reflects its abundance in the mixture. These can then conceptually be used to determine which proteins are differentially expressed under different experimental conditions. We propose an EM approach to identify differentially expressed proteins using an inferential strategy that accounts for uncertainty in matching spots to proteins across gels. The underlying mixture model has trivariate Gaussian components. The application of the EM is however, not straightforward, with the main difficulty lying in the E-step calculations because of the dependent structure of proteins within each gel. Therefore, the usual model-based clustering approach is inapplicable, and an MCMC approach is employed. Through data-based simulation, we demonstrate that our proposed method effectively accounts for uncertainty in spot matching and more successfully distinguishes differentially and non-differentially expressed proteins than a naïve t-test which ignores uncertainty in spot matching.</p>
dc.description.comments <p>This is a manuscript of an article from <em>Sankhya B</em> 73 (2011): 123, doi: <a href="http://dx.doi.org/10.1007/s13571-011-0016-x" target="_blank">10.1007/s13571-011-0016-x</a>. The final publication is available at Springer via http://dx.doi.org/<a href="http://dx.doi.org/10.1007/s13571-011-0016-x" target="_blank">10.1007/s13571-011-0016-x.</a></p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/stat_las_pubs/74/
dc.identifier.articleid 1074
dc.identifier.contextkey 8821026
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_pubs/74
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/90675
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/stat_las_pubs/74/2011_MaitraR_AccountingSpotMatching.pdf|||Sat Jan 15 01:47:33 UTC 2022
dc.source.uri 10.1007/s13571-011-0016-x
dc.subject.disciplines Statistics and Probability
dc.subject.keywords s Conditional point process simulation
dc.subject.keywords Isoelectric points
dc.subject.keywords Molecular weights
dc.subject.keywords ROC curves
dc.subject.keywords Observed information matrix
dc.subject.keywords EM algorithm
dc.subject.keywords Markov chain Monte Carlo
dc.subject.keywords Gaussian mixture model
dc.title Accounting for spot matching uncertainty in the analysis of proteomics data from two-dimensional gel electrophoresis
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 7d86677d-f28f-4ab1-8cf7-70378992f75b
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
File
Original bundle
Now showing 1 - 1 of 1
Name:
2011_MaitraR_AccountingSpotMatching.pdf
Size:
862.87 KB
Format:
Adobe Portable Document Format
Description:
Collections