Journal: BMC Bioinformatics

Article Title: SIMAGE : si mulation of DNA- m icro a rray g ene e xpression data

doi: 10.1186/1471-2105-7-205

Figure Lengend Snippet: Comparison of the properties of different DNA-microarray simulation models described in literature. '+' and '-' indicate availability of the indicated feature in the specified model. Note that the modeling of features in the specific models is usually not the same.

Article Snippet: To illustrate the use of SIMAGE in drawing meaningful conclusions about the design and analysis of DNA microarray experiments we show a number of examples based on DNA microarray data generated within the MolGen department.

Techniques: Comparison, Gene Expression, Software

Journal: BMC Bioinformatics

Article Title: SIMAGE : si mulation of DNA- m icro a rray g ene e xpression data

doi: 10.1186/1471-2105-7-205

Figure Lengend Snippet: Distribution of the deviations of several of the model parameters estimated from 100 simulated DNA-microarray slides. The deviation is calculated as (estimate - true value) / (standard deviation of 100 estimates).

Article Snippet: To illustrate the use of SIMAGE in drawing meaningful conclusions about the design and analysis of DNA microarray experiments we show a number of examples based on DNA microarray data generated within the MolGen department.

Techniques: Microarray, Standard Deviation

Journal: BMC Bioinformatics

Article Title: SIMAGE : si mulation of DNA- m icro a rray g ene e xpression data

doi: 10.1186/1471-2105-7-205

Figure Lengend Snippet: Distribution of p -values of a DNA-microarray experiment simulated by SIMAGE . Data for 2200 genes, in 6 slides with technical duplicates hybridized in dye-swaps, was simulated using the MolGen experiment profile (supplementary Table T1) with some changes: π - = 1% and π + = 2%, μ - = -2 and μ + = 2), σ bg = 700, and s = 30 % × μ . The main graph shows the resulting ratios after normalization plotted versus the p -value. The graph was simplified by removing genes with ratios between 2/3 and 3/2. The 66 genes for which differential expressions were modeled are depicted by blue diamonds. The remaining genes are depicted in purple squares. The small graph on the right demonstrates the reversed p -value dependency on the average signal for the 66 differentially expressed genes modeled. The average signal was calculated for each of the 66 genes over the maximum of 12 normalized measurements. Normalization was performed using Lowess normalization and differential expression tests were performed with the non-Bayesian Cyber-T implementation of a variant of the t -test [3]. The Cyber-T test provides the p -values, which indicate the probability that a given ratio is not differential caused by chance. Genes with less than 8 measurements were excluded from these tests and assigned a p -value of 1, in order to be able to present these genes in the graph.

Article Snippet: To illustrate the use of SIMAGE in drawing meaningful conclusions about the design and analysis of DNA microarray experiments we show a number of examples based on DNA microarray data generated within the MolGen department.

Techniques: Microarray, Quantitative Proteomics, Variant Assay

Journal: BMC Bioinformatics

Article Title: SIMAGE : si mulation of DNA- m icro a rray g ene e xpression data

doi: 10.1186/1471-2105-7-205

Figure Lengend Snippet: Estimation of parameters from the simulation of 100 DNA-microarray slides. The mentioned deviations are the number of estimated standard-deviations that the estimated mean, respectively median, lie away from the true value of the parameter.

Article Snippet: To illustrate the use of SIMAGE in drawing meaningful conclusions about the design and analysis of DNA microarray experiments we show a number of examples based on DNA microarray data generated within the MolGen department.

Techniques: