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Table 1 Analysis of general, unconstrained variance vs. nested, constrained variance models

From: Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels and spotted DNA microarrays

Data

Model*

Genes

s / gene**

Mm

Parameters

BIC***

Townsend et al. (2003)

AU

4506

5.2

33312.6

7

-11147.1

Townsend et al. (2003)

AC

5759

4.1

21296.8

4

-4108.8

Townsend et al. (2003)

AV

5759

4.8

21365.8

4

-4039.8

Townsend et al. (2003)

MU

4506

7.0

33969.2

7

-10490.6

Townsend et al. (2003)

MC

5759

5.7

21469.2

4

-3936.4

Townsend et al. (2003)

MV

5759

6.2

21459.1

4

-3946.5

Sudarsanam et al. (2000)

AU

4756

3.5

19874.9

5

-1053.6

Sudarsanam et al. (2000)

AC

5888

3.2

16199.2

3

502.9

Sudarsanam et al. (2000)

AV

5888

3.6

16200.4

3

504.1

Sudarsanam et al. (2000)

MU

4756

4.4

20229.8

5

-698.7

Sudarsanam et al. (2000)

MC

5888

4.1

16494.4

3

798.0

Sudarsanam et al. (2000)

MV

5888

4.7

16370.7

3

674.3

  1. * (A)dditive or (M)ultiplicative error, with (U)nconstrained variances, a common (C)oefficient of variation, or a common (V)ariance. ** seconds of processor time on a dual 1 GHz PowerPC G4 *** Bayesian Information Criterion