Project description:Microarray technology has enabled the measurement of comprehensive transcriptomic information. However, each data entry may reflect trivial individual differences among samples and also contain technical noise. Therefore, the certainty of each observed difference should be confirmed at earlier steps of the analyses, and statistical tests are frequently used for this purpose. Since a microarray measures a huge number of genes and the results are processed simultaneously, concerns regarding problems of multiplicity have been raised to the tests. To deal with these problems, several methodologies have been proposed, making the tests very conservative. Indeed, arbitrary tuning of the test threshold has also been introduced to relax the test conditions. However, the appropriateness of the multiplicity problems as well as the compensation methods has not been confirmed. The appropriateness of the compensation methods was checked by means of coincidence of the premises of the methodologies with the observed characteristics found in real data of two typical platforms of microarray analysis. Normality was observed in within-group data variations, supporting applications of parametric tests. However, genes displayed their own tendencies in the magnitude of variations, and the distributions of P-values were rather complex and varied; these characteristics are inconsistent with the premises of the compensation methodologies. Additionally, the appropriateness of the proposed multiplicities is reconsidered. When we observed differences in the transcriptome, the family-wise error rate should not be considered, since analyses at higher levels would not be influenced by a few false positives among the huge numbers of true information. Likely, concerns for a false discovery rate are not suitable for the point null hypotheses on expression levels, since the rate of true null hypotheses should be rare in contradiction to the premise of the methodology. Although compensation methods have been recommended to deal with the problem of multiplicity, the compensations are actually inappropriate for many of the applications of transcriptome analyses. Compensations are not only unnecessary, but will increase the occurrence of false negative errors, and arbitrary adjustment of the threshold damages the objectivity of the tests. Rather, the results of parametric tests should be evaluated directly. This SuperSeries is composed of the SubSeries listed below.
Project description:We report transcriptional profiles of placentas from systemic lupus erythematosus pregnancies and normal full-term pregnancies. We recruited 8 pregnant patients with SLE, and 8 age-matched healthy pregnant women as normal controls. RNA-seq strand-specific libraries were constructed using the VAHTS Total RNA-seq (H/M/R)Library Prep Kit. Differentially expressed genes were identified using Cuffdiff. The P-value significance threshold in multiple tests was set by the false discovery rate (FDR). The fold-changes were also estimated according to the FPKM in each sample.The differentially expressed genes were selected using the following filter criteria: FDR <0.05 and fold-change >2.
Project description:Through RNA-seq, we report endothelial cells from mutants had 1063 up-regulated and 132 down-regulated genes (>2.0 fold with false discovery rate <0.001) when compared to siblings.
Project description:Biological replicate of EV23+24. The two samples in this series are complementary hybridizations in a dye-swap analysis. Below is the normalized result of the paired dye swap samples VC110 and VC112. The ANOVA model of Kerr, Martin and Churchill (2000) was used to analyze the data from the dye-swap experiments, with terms included to account for gene, dye-by-gene, treatment-by-gene, and random error terms. To account for the number of hypothesis tests being made, and thus provide some level of error rate control, significance was assessed using a false discovery rate (FDR) controlling method. The step-up procedure of Benjamini and Hochberg (1995) was used to control the FDR below alpha = 0.01. For the purposes of this experiment, the hypotheses were assumed to be independent. Features found to be significantly enriched for DNA methylation after hypothesis-testing with a controlled error rate are flagged in the column. Standard errors and P-values are not available. Keywords: other
Project description:Technical replicate of EV33+34. The two samples in this series are complementary hybridizations in a dye-swap analysis. Below is the normalized result of the paired dye swap samples EV39 and EV40. The ANOVA model of Kerr, Martin and Churchill (2000) was used to analyze the data from the dye-swap experiments, with terms included to account for gene, dye-by-gene, treatment-by-gene, and random error terms. To account for the number of hypothesis tests being made, and thus provide some level of error rate control, significance was assessed using a false discovery rate (FDR) controlling method. The step-up procedure of Benjamini and Hochberg (1995) was used to control the FDR below alpha = 0.01. For the purposes of this experiment, the hypotheses were assumed to be independent. Features found to be significantly enriched for DNA methylation after hypothesis-testing with a controlled error rate are flagged in the column. Standard errors and P-values are not available. Keywords: other
Project description:Biological replicate of EV33+34. The two samples in this series are complementary hybridizations in a dye-swap analysis. Below is the normalized result of the paired dye swap samples VC109 and VC110. The ANOVA model of Kerr, Martin and Churchill (2000) was used to analyze the data from the dye-swap experiments, with terms included to account for gene, dye-by-gene, treatment-by-gene, and random error terms. To account for the number of hypothesis tests being made, and thus provide some level of error rate control, significance was assessed using a false discovery rate (FDR) controlling method. The step-up procedure of Benjamini and Hochberg (1995) was used to control the FDR below alpha = 0.01. For the purposes of this experiment, the hypotheses were assumed to be independent. Features found to be significantly enriched for DNA methylation after hypothesis-testing with a controlled error rate are flagged in the column. Standard errors and P-values are not available. Keywords: other
Project description:The two samples in this series are complementary hybridizations in a dye-swap analysis. Below is the normalized result of the paired dye swap samples EV33 and EV34. The ANOVA model of Kerr, Martin and Churchill (2000) was used to analyze the data from the dye-swap experiments, with terms included to account for gene, dye-by-gene, treatment-by-gene, and random error terms. To account for the number of hypothesis tests being made, and thus provide some level of error rate control, significance was assessed using a false discovery rate (FDR) controlling method. The step-up procedure of Benjamini and Hochberg (1995) was used to control the FDR below alpha = 0.01. For the purposes of this experiment, the hypotheses were assumed to be independent. Features found to be significantly enriched for DNA methylation after hypothesis-testing with a controlled error rate are flagged in the column. Standard errors and P-values are not available. Keywords: other
Project description:With a filter of false-discovery rate less than 0.1 and fold change greater than 1.5, 115 genes were found to be up- and 137 were down-regulated in alveolar macrophages during Pneumocystis carinii infection.
Project description:The two samples in this series are complementary hybridizations in a dye-swap analysis. Below is the normalized result of the paired dye swap samples EV23 and EV24. The ANOVA model of Kerr, Martin and Churchill (2000) was used to analyze the data from the dye-swap experiments, with terms included to account for gene, dye-by-gene, treatment-by-gene, and random error terms. To account for the number of hypothesis tests being made, and thus provide some level of error rate control, significance was assessed using both family-wise error rate (FWER) and false discovery rate (FDR) controlling methods. The step-down multiple comparisons procedure of Holm (1979) was used to control the FWER below alpha = 0.01, while the step-up procedure of Benjamini and Hochberg (1995) was used to control the FDR below alpha = 0.01. For the purposes of this experiment, the hypotheses were assumed to be independent. Features found to be significantly enriched for DNA methylation after hypothesis-testing with a controlled error rate are flagged in the last two columns. Keywords: other