Using Generalized Procrustes Analysis (GPA) for normalization of cDNA microarray data

<p>Abstract</p> <p>Background</p> <p>Normalization is essential in dual-labelled microarray data analysis to remove non-biological variations and systematic biases. Many normalization methods have been used to remove such biases within slides (Global, Lowess) and across slides (Scale, Quantile and VSN). However, all these popular approaches have critical assumptions about data distribution, which is often not valid in practice.</p> <p>Results</p> <p>In this study, we propose a novel assumption-free normalization method based on the Generalized Procrustes Analysis (GPA) algorithm. Using experimental and simulated normal microarray data and boutique array data, we systemically evaluate the ability of the GPA method in normalization compared with six other popular normalization methods including Global, Lowess, Scale, Quantile, VSN, and one boutique array-specific housekeeping gene method. The assessment of these methods is based on three different empirical criteria: across-slide variability, the Kolmogorov-Smirnov (K-S) statistic and the mean square error (MSE). Compared with other methods, the GPA method performs effectively and consistently better in reducing across-slide variability and removing systematic bias.</p> <p>Conclusion</p> <p>The GPA method is an effective normalization approach for microarray data analysis. In particular, it is free from the statistical and biological assumptions inherent in other normalization methods that are often difficult to validate. Therefore, the GPA method has a major advantage in that it can be applied to diverse types of array sets, especially to the boutique array where the majority of genes may be differentially expressed.</p

Mural granulosa cell gene expression associated with oocyte developmental competence

<p>Abstract</p> <p>Background</p> <p>Ovarian follicle development is a complex process. Paracrine interactions between somatic and germ cells are critical for normal follicular development and oocyte maturation. Studies have suggested that the health and function of the granulosa and cumulus cells may be reflective of the health status of the enclosed oocyte. The objective of the present study is to assess, using an <it>in vivo </it>immature rat model, gene expression profile in granulosa cells, which may be linked to the developmental competence of the oocyte. We hypothesized that expression of specific genes in granulosa cells may be correlated with the developmental competence of the oocyte.</p> <p>Methods</p> <p>Immature rats were injected with eCG and 24 h thereafter with anti-eCG antibody to induce follicular atresia or with pre-immune serum to stimulate follicle development. A high percentage (30-50%, normal developmental competence, NDC) of oocytes from eCG/pre-immune serum group developed to term after embryo transfer compared to those from eCG/anti-eCG (0%, poor developmental competence, PDC). Gene expression profiles of mural granulosa cells from the above oocyte-collected follicles were assessed by Affymetrix rat whole genome array.</p> <p>Results</p> <p>The result showed that twelve genes were up-regulated, while one gene was down-regulated more than 1.5 folds in the NDC group compared with those in the PDC group. Gene ontology classification showed that the up-regulated genes included lysyl oxidase (<it>Lox</it>) and nerve growth factor receptor associated protein 1 (<it>Ngfrap1</it>), which are important in the regulation of protein-lysine 6-oxidase activity, and in apoptosis induction, respectively. The down-regulated genes included glycoprotein-4-beta galactosyltransferase 2 (<it>Ggbt2</it>), which is involved in the regulation of extracellular matrix organization and biogenesis.</p> <p>Conclusions</p> <p>The data in the present study demonstrate a close association between specific gene expression in mural granulosa cells and the developmental competence of oocytes. This finding suggests that the most differentially expressed gene, lysyl oxidase, may be a candidate biomarker of oocyte health and useful for the selection of good quality oocytes for assisted reproduction.</p

Defining Global Neuroendocrine Gene Expression Patterns Associated with Reproductive Seasonality in Fish

Many vertebrates, including the goldfish, exhibit seasonal reproductive rhythms, which are a result of interactions between external environmental stimuli and internal endocrine systems in the hypothalamo-pituitary-gonadal axis. While it is long believed that differential expression of neuroendocrine genes contributes to establishing seasonal reproductive rhythms, no systems-level investigation has yet been conducted. gamma2 receptor, calmodulin, and aromatase b by independent samplings of goldfish brains from six seasonal time points and real-time PCR assays.Using both theoretical and experimental strategies, we report for the first time global gene expression patterns throughout a breeding season which may account for dynamic neuroendocrine regulation of seasonal reproductive development

Large-Scale Evolutionary Multi-Objective Optimization Based on Direction Vector Sampling

The large-scale multi-objective optimization problem is characterized by a large decision space. How to design an efficient optimization algorithm that can search a large decision space and find the global optimum in the objective space is a very challenging problem at present. In order to solve this problem, this paper proposes a sampling strategy based on direction vectors, which takes into account both convergence and diversity. First, select some excellent individuals who are close to the ideal point based on the reference vector. Secondly, construct a three-way search direction vector using the boundary point and an additional center point, and execute a directional sampling strategy called the convergence-related sampling strategy to improve the convergence of the algorithm. After, the direction vector is constructed among excellent individuals and executes a directional sampling strategy called the diversity-related sampling strategy to maintain the diversity of the population. Finally, the adjustment strategy of the reference vector in the Reference Vector Guidance Algorithm (RVEA) is adopted to adjust the reference vector. Numerical experiments are performed on large-scale multi-objective benchmark problem sets with 500, 1000, and 2000 decision variables and compared with the state-of-the-art algorithms. Experimental results show that the algorithm proposed in this paper is effective and can obtain solutions that are significantly better than those of the compared algorithms

Rebamipide with Proton Pump Inhibitors (PPIs) versus PPIs Alone for the Treatment of Endoscopic Submucosal Dissection-Induced Ulcers: A Meta-analysis

Objective. To contrast the effect of rebamipide with proton pump inhibitors (PPIs) versus PPIs alone for the treatment of endoscopic submucosal dissection (ESD-) induced ulcers. Methods. PubMed, Embase, the Cochrane library, the WanFang database, and China National Knowledge Infrastructure (CNKI) were searched to identify studies that met the inclusion criteria. Results. Nine randomized controlled trials (RCTs) were recognized, including 1170 patients. In general, rebamipide plus PPIs acted better than PPIs alone against ESD-induced ulcers at four weeks (RR=1.42, 95% CI: 1.13-1.78, P=0.003) but showed no significant differences at eight weeks (RR=1.03, 95% CI: 0.97-1.10, P=0.315). The use of rebamipide plus PPIs was superior to PPIs alone for ESD-induced ulcers greater than 20 mm in size (20-40 mm: RR=1.98, 95% CI: 1.22-3.23, P=0.006; >40 mm: RR=5.14, 95% CI: 1.49-17.74, P=0.010). In addition, rebamipide plus PPI therapy was discovered to be significantly more effective than PPIs alone for lower ESD-induced ulcers (RR=1.82, 95% CI: 1.04-3.20, P=0.037). There were no significant differences between the treatment groups with the ulcer reduction rate. Conclusion. Evidences now available show rebamipide plus PPIs is practical for protecting against ESD-induced ulcers at four weeks but not at eight weeks, especially large ulcers (>20 mm). However, we still need more high-quality RCTs in the future to supplement our conclusions

Using Generalized Procrustes Analysis (GPA) for normalization of cDNA microarray data-3

Slides with 90% up-regulated genes at 10 fold and 10% down-regulated genes at 2 fold. Four slides represented by four colours (blue, red, pink, green) were randomly selected to show their M-A plots after each GPA transformation procedure.<p><b>Copyright information:</b></p><p>Taken from "Using Generalized Procrustes Analysis (GPA) for normalization of cDNA microarray data"</p><p>http://www.biomedcentral.com/1471-2105/9/25</p><p>BMC Bioinformatics 2008;9():25-25.</p><p>Published online 16 Jan 2008</p><p>PMCID:PMC2275243.</p><p></p

Using Generalized Procrustes Analysis (GPA) for normalization of cDNA microarray data-2

<p><b>Copyright information:</b></p><p>Taken from "Using Generalized Procrustes Analysis (GPA) for normalization of cDNA microarray data"</p><p>http://www.biomedcentral.com/1471-2105/9/25</p><p>BMC Bioinformatics 2008;9():25-25.</p><p>Published online 16 Jan 2008</p><p>PMCID:PMC2275243.</p><p></p

Using Generalized Procrustes Analysis (GPA) for normalization of cDNA microarray data-4

Ocedure. The blue points represent raw data; pink points represent reference slide; red, green and purple points represent data points after translation, rotation and scaling, respectively; (b) shows how the M-A plots for four slides represented by four colours (blue, red, pink, green) transformed after each GPA transformation procedure. The SIMAGE method was used to simulate the microarray data set used here, which includes 50 slides with 10% differentially expressed genes and ratio of up-regulated to down-regulated genes is 1:1.<p><b>Copyright information:</b></p><p>Taken from "Using Generalized Procrustes Analysis (GPA) for normalization of cDNA microarray data"</p><p>http://www.biomedcentral.com/1471-2105/9/25</p><p>BMC Bioinformatics 2008;9():25-25.</p><p>Published online 16 Jan 2008</p><p>PMCID:PMC2275243.</p><p></p