Use of Mixture Models in a Microarray-Based Screening Procedure for Detecting Differentially Represented Yeast Mutants : Statistical Applications in Genetics and Molecular Biology Jump to ContentJump to Main Navigation
Show Summary Details

Statistical Applications in Genetics and Molecular Biology

Editor-in-Chief: Stumpf, Michael P.H.

IMPACT FACTOR increased in 2015: 1.265
5-year IMPACT FACTOR: 1.423
Rank 42 out of 123 in category Statistics & Probability in the 2015 Thomson Reuters Journal Citation Report/Science Edition

SCImago Journal Rank (SJR) 2015: 0.954
Source Normalized Impact per Paper (SNIP) 2015: 0.554
Impact per Publication (IPP) 2015: 1.061

Mathematical Citation Quotient (MCQ) 2015: 0.06

99,00 € / $149.00 / £75.00*

See all formats and pricing


Select Volume and Issue
Loading journal volume and issue information...

30,00 € / $42.00 / £23.00

Get Access to Full Text

Use of Mixture Models in a Microarray-Based Screening Procedure for Detecting Differentially Represented Yeast Mutants

Rafael A Irizarry1 / Siew Loon Ooi2 / Zhijin Wu3 / Jef D Boeke4

1Johns Hopkins University

2Johns Hopkins University

3Johns Hopkins University

4Johns Hopkins University

Citation Information: Statistical Applications in Genetics and Molecular Biology. Volume 2, Issue 1, ISSN (Online) 1544-6115, DOI: 10.2202/1544-6115.1002, March 2003

Publication History

Published Online:

We describe the use of a statistical model in a genome-wide microarray-based yeast genetic screen performed by imposing different genetic selections on thousands of yeast mutants in parallel. A mixture model is fitted to data obtained from oligonucleotide arrays hybridized to 20-mer oligonucleotide ``barcodes'' and a procedure based on the fitted model is used to search for mutants differentially represented under experimental and control conditions. The fitted stochastic model provides a way to assess uncertainty. We demonstrate the usefulness of the model by applying it to the problem of screening for components of the nonhomologous end joining (NHEJ) pathway and identified known components of the NHEJ pathway.

Keywords: Differential Representation; Mixture Model; Oligonucleotide Microarray; Weighted z-test

Citing Articles

Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.

Anait S. Levenson, Avinash Kumar, and Xu Zhang
Cancer and Metastasis Reviews, 2014, Volume 33, Number 4, Page 929
Plant, Cell & Environment, 2015, Volume 38, Number 1, Page 73
G. K. Perera, C. Ainali, E. Semenova, C. Hundhausen, G. Barinaga, D. Kassen, A. E. Williams, M. M. Mirza, M. Balazs, X. Wang, R. S. Rodriguez, A. Alendar, J. Barker, S. Tsoka, W. Ouyang, and F. O. Nestle
Science Translational Medicine, 2014, Volume 6, Number 223, Page 223ra22
Laurent Bonneau, Stéphanie Huguet, Daniel Wipf, Nicolas Pauly, and Hoai-Nam Truong
New Phytologist, 2013, Volume 199, Number 1, Page 188
Siew Loon Ooi, Xuewen Pan, Brian D. Peyser, Ping Ye, Pamela B. Meluh, Daniel S. Yuan, Rafael A. Irizarry, Joel S. Bader, Forrest A. Spencer, and Jef D. Boeke
Trends in Genetics, 2006, Volume 22, Number 1, Page 56
Guri Feten, Trygve Almøy, Lars Snipen, Ågot Aakra, O. Ludvig Nyquist, and Are H. Aastveit
Biometrical Journal, 2007, Volume 49, Number 2, Page 242

Comments (0)

Please log in or register to comment.