A probabilistic treatment of the missing spot problem in 2D gel electrophoresis experiments

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Krogh, MortenLund University,Lunds universitet,Beräkningsbiologi och biologisk fysik - Genomgår omorganisation,Institutionen för astronomi och teoretisk fysik - Genomgår omorganisation,Naturvetenskapliga fakulteten,Computational Biology and Biological Physics - Undergoing reorganization,Department of Astronomy and Theoretical Physics - Undergoing reorganization,Faculty of Science (author)

A probabilistic treatment of the missing spot problem in 2D gel electrophoresis experiments

Article/chapterEnglish2007

Publisher, publication year, extent ...

2007-07-11
American Chemical Society (ACS),2007

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LIBRIS-ID:oai:lup.lub.lu.se:6c878b1c-f8e8-4973-bda6-8a1cfa05643c
https://lup.lub.lu.se/record/646358URI
https://doi.org/10.1021/pr070137pDOI

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Language:English
Summary in:English

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SwePubSwePub

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Subject category:art swepub-publicationtype
Subject category:ref swepub-contenttype

Notes

Two-dimensional SIDS-PAGE gel electrophoresis using post-run staining is widely used to measure the abundances of thousands of protein spots simultaneously. Usually, the protein abundances of two or more biological groups are compared using biological and technical replicates. After gel separation and staining, the spots are detected, spot volumes are quantified, and spots are matched across gels. There are almost always many missing values in the resulting data set. The missing values arise either because the corresponding proteins have very low abundances (or are absent) or because of experimental errors such as incomplete/over focusing in the first dimension or varying run times in the second dimension as well as faulty spot detection and matching. In this study, we show that the probability for a spot to be missing can be modeled by a logistic regression function of the logarithm of the volume. Furthermore, we present an algorithm that takes a set of gels with technical and biological replicates as input and estimates the average protein abundances in the biological groups from the number of missing spots and measured volumes of the present spots using a maximum likelihood approach. Confidence intervals for abundances and p-values for differential expression between two groups are calculated using bootstrap sampling. The algorithm is compared to two standard approaches, one that discards missing values and one that sets all missing values to zero. We have evaluated this approach in two different gel data sets of different biological origin. An F-program, implementing the algorithm, is freely available at httP://bioinfo.thep.lu.se/MissingValues2Dgels.html.

Subject headings and genre

MEDICIN OCH HÄLSOVETENSKAP Klinisk medicin Neurologi hsv//swe
MEDICAL AND HEALTH SCIENCES Clinical Medicine Neurology hsv//eng
MEDICIN OCH HÄLSOVETENSKAP Klinisk medicin Endokrinologi och diabetes hsv//swe
MEDICAL AND HEALTH SCIENCES Clinical Medicine Endocrinology and Diabetes hsv//eng
missing values
maximum likelihood
2D-PAGE

Added entries (persons, corporate bodies, meetings, titles ...)

Fernandez, CelineLund University,Lunds universitet,Molekylär endokrinologi,Forskargrupper vid Lunds universitet,Molecular Endocrinology,Lund University Research Groups(Swepub:lu)medk-cfe (author)
Teilum, MariaLund University,Lunds universitet,Sektion IV,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Section IV,Department of Clinical Sciences, Lund,Faculty of Medicine(Swepub:lu)expb-mwr (author)
Bengtsson, Sofia (author)
James, PeterLund University,Lunds universitet,Institutionen för immunteknologi,Institutioner vid LTH,Lunds Tekniska Högskola,Department of Immunotechnology,Departments at LTH,Faculty of Engineering, LTH(Swepub:lu)elma-pja (author)
Beräkningsbiologi och biologisk fysik - Genomgår omorganisationInstitutionen för astronomi och teoretisk fysik - Genomgår omorganisation (creator_code:org_t)

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In:Journal of Proteome Research: American Chemical Society (ACS)6:8, s. 3335-33431535-38931535-3907

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