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An empirical bayesian method for detecting differentially expressed genes using EST data.

You N, Liu J, Mao CX - Int J Plant Genomics (2008)

Bottom Line: An empirical Bayesian method is introduced in which gene expression patterns are estimated and used to define detection statistics.Significantly differentially expressed genes can be declared given detection statistics.Simulation is done to evaluate the performance of proposed method.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics, University of California, Riverside, 92521, USA.

ABSTRACT
Detection of differentially expressed genes from expressed sequence tags (ESTs) data has received much attention. An empirical Bayesian method is introduced in which gene expression patterns are estimated and used to define detection statistics. Significantly differentially expressed genes can be declared given detection statistics. Simulation is done to evaluate the performance of proposed method. Two real applications are studied.

No MeSH data available.


Related in: MedlinePlus

Simulation results of Fisher's exact test (∘), χ2 test (Δ), AC statistic(+), R statistic(×), and theproposed statistic (•) in detectingSDE genes using two EST samples of different sizes.
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Related In: Results  -  Collection


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fig2: Simulation results of Fisher's exact test (∘), χ2 test (Δ), AC statistic(+), R statistic(×), and theproposed statistic (•) in detectingSDE genes using two EST samples of different sizes.

Mentions: In the second four experiments, (s1, s2) = (2000, 4000), (4000, 2000), (2000, 4000), and (4000, 2000) respectively,and the results are presented in Figure 2. Note that G1 = Gamma(3, 0.1) and G2 = Beta(2, 2) in Figures 2(a)and 2(b) and G1 = U(0, 10) and G2 = Beta(2, 1) in Figures 2(c)and 2(d). The proposed method is usually the best one among all methodsstudied.


An empirical bayesian method for detecting differentially expressed genes using EST data.

You N, Liu J, Mao CX - Int J Plant Genomics (2008)

Simulation results of Fisher's exact test (∘), χ2 test (Δ), AC statistic(+), R statistic(×), and theproposed statistic (•) in detectingSDE genes using two EST samples of different sizes.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2277491&req=5

fig2: Simulation results of Fisher's exact test (∘), χ2 test (Δ), AC statistic(+), R statistic(×), and theproposed statistic (•) in detectingSDE genes using two EST samples of different sizes.
Mentions: In the second four experiments, (s1, s2) = (2000, 4000), (4000, 2000), (2000, 4000), and (4000, 2000) respectively,and the results are presented in Figure 2. Note that G1 = Gamma(3, 0.1) and G2 = Beta(2, 2) in Figures 2(a)and 2(b) and G1 = U(0, 10) and G2 = Beta(2, 1) in Figures 2(c)and 2(d). The proposed method is usually the best one among all methodsstudied.

Bottom Line: An empirical Bayesian method is introduced in which gene expression patterns are estimated and used to define detection statistics.Significantly differentially expressed genes can be declared given detection statistics.Simulation is done to evaluate the performance of proposed method.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics, University of California, Riverside, 92521, USA.

ABSTRACT
Detection of differentially expressed genes from expressed sequence tags (ESTs) data has received much attention. An empirical Bayesian method is introduced in which gene expression patterns are estimated and used to define detection statistics. Significantly differentially expressed genes can be declared given detection statistics. Simulation is done to evaluate the performance of proposed method. Two real applications are studied.

No MeSH data available.


Related in: MedlinePlus