932 resultados para data reduction by factor analysis


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Background: We use an approach based on Factor Analysis to analyze datasets generated for transcriptional profiling. The method groups samples into biologically relevant categories, and enables the identification of genes and pathways most significantly associated to each phenotypic group, while allowing for the participation of a given gene in more than one cluster. Genes assigned to each cluster are used for the detection of pathways predominantly activated in that cluster by finding statistically significant associated GO terms. We tested the approach with a published dataset of microarray experiments in yeast. Upon validation with the yeast dataset, we applied the technique to a prostate cancer dataset. Results: Two major pathways are shown to be activated in organ-confined, non-metastatic prostate cancer: those regulated by the androgen receptor and by receptor tyrosine kinases. A number of gene markers (HER3, IQGAP2 and POR1) highlighted by the software and related to the later pathway have been validated experimentally a posteriori on independent samples. Conclusion: Using a new microarray analysis tool followed by a posteriori experimental validation of the results, we have confirmed several putative markers of malignancy associated with peptide growth factor signalling in prostate cancer and revealed others, most notably ERRB3 (HER3). Our study suggest that, in primary prostate cancer, HER3, together or not with HER4, rather than in receptor complexes involving HER2, could play an important role in the biology of these tumors. These results provide new evidence for the role of receptor tyrosine kinases in the establishment and progression of prostate cancer.

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A szervezeti kultúraváltozók nem függetlenek egymástól. A tanulmány a GLOBE társadalmi kultúra, társadalmi értékek és a kettő különbségéből képzett differenciaváltozók faktoranalízisével kísérel meg főfaktorokat meghatározni és azokat értelmezni. / === / The cultural variables are not independent. This paper describes and discusses consolidated cultural variables computed by factor analysis from 9 original GLOBE variables of societal paracices, societal values, and differentiation scales.

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P>The use of seven domains for the Oral Health Impact Profile (OHIP)-EDENT was not supported for its Brazilian version, making data interpretation in clinical settings difficult. Thus, the aim of this study was to assess patients` responses for the translated OHIP-EDENT in a group of edentulous subjects and to develop factor scales for application in future studies. Data from 103 conventional and implant-retained complete denture wearers (36 men, mean age of 69 center dot 1 +/- 10 center dot 3 years) were assessed using the Brazilian version of the OHIP-EDENT. Oral health-related quality of life domains were identified by factor analysis using principal component analysis as the extraction method, followed by varimax rotation. Factor analysis identified four factors that accounted for 63% of the 19 items total variance, named masticatory discomfort and disability (four items), psychological discomfort and disability (five items), social disability (five items) and oral pain and discomfort (five items). Four factors/domains of the Brazilian OHIP-EDENT version represent patient-important aspects of oral health-related quality of life.

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Background Diet composition is one of the factors that may contribute to intraindividual variability in the anticoagulant response to warfarin. Aim of the study To determine the associations between food pattern and anticoagulant response to warfarin in a group of Brazilian patients with vascular disease. Methods Recent and usual food intakes were assessed in 115 patients receiving warfarin; and corresponding plasma phylloquinone (vitamin K-1), serum triglyceride concentrations, prothrombin time (PT), and International Normalized Ratio (INR) were determined. A factor analysis was used to examine the association of specific foods and biochemical variables with anticoagulant data. Results Mean age was 59 +/- 15 years. Inadequate anticoagulation, defined as values of INR 2 or 3, was found in 48% of the patients. Soybean oil and kidney beans were the primary food sources of phylloquinone intake. Factor analysis yielded four separate factors, explaining 56.4% of the total variance in the data set. The factor analysis revealed that intakes of kidney beans and soybean oil, 24-h recall of phylloquinone intake, PT and INR loaded significantly on factor 1. Triglycerides, PT, INR, plasma phylloquinone, and duration of anticoagulation therapy loaded on factor 3. Conclusion Fluctuations in phylloquinone intake, particularly from kidney beans, and plasma phylloquinone concentrations were associated with variation in measures of anticoagulation (PT and INR) in a Brazilian group of patients with vascular disease.

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Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = Λf + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix Λ.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ΛΛT + ψ (2)where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as theloadings matrix Λ are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data

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Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr) transformation to obtain the random vector y of dimension D. The factor model is then y = Λf + e (1) with the factors f of dimension k < D, the error term e, and the loadings matrix Λ. Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysis model (1) can be written as Cov(y) = ΛΛT + ψ (2) where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as the loadings matrix Λ are estimated from an estimation of Cov(y). Given observed clr transformed data Y as realizations of the random vector y. Outliers or deviations from the idealized model assumptions of factor analysis can severely effect the parameter estimation. As a way out, robust estimation of the covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), see Pison et al. (2003). Well known robust covariance estimators with good statistical properties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), rely on a full-rank data matrix Y which is not the case for clr transformed data (see, e.g., Aitchison, 1986). The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves this singularity problem. The data matrix Y is transformed to a matrix Z by using an orthonormal basis of lower dimension. Using the ilr transformed data, a robust covariance matrix C(Z) can be estimated. The result can be back-transformed to the clr space by C(Y ) = V C(Z)V T where the matrix V with orthonormal columns comes from the relation between the clr and the ilr transformation. Now the parameters in the model (2) can be estimated (Basilevsky, 1994) and the results have a direct interpretation since the links to the original variables are still preserved. The above procedure will be applied to data from geochemistry. Our special interest is on comparing the results with those of Reimann et al. (2002) for the Kola project data

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The most influential theoretical account in time psychophysics assumes the existence of a unitary internal clock based on neural counting. The distinct timing hypothesis, on the other hand, suggests an automatic timing mechanism for processing of durations in the sub-second range and a cognitively controlled timing mechanism for processing of durations in the range of seconds. Although several psychophysical approaches can be applied for identifying the internal structure of interval timing in the second and sub-second range, the existing data provide a puzzling picture of rather inconsistent results. In the present chapter, we introduce confirmatory factor analysis (CFA) to further elucidate the internal structure of interval timing performance in the sub-second and second range. More specifically, we investigated whether CFA would rather support the notion of a unitary timing mechanism or of distinct timing mechanisms underlying interval timing in the sub-second and second range, respectively. The assumption of two distinct timing mechanisms which are completely independent of each other was not supported by our data. The model assuming a unitary timing mechanism underlying interval timing in both the sub-second and second range fitted the empirical data much better. Eventually, we also tested a third model assuming two distinct, but functionally related mechanisms. The correlation between the two latent variables representing the hypothesized timing mechanisms was rather high and comparison of fit indices indicated that the assumption of two associated timing mechanisms described the observed data better than only one latent variable. Models are discussed in the light of the existing psychophysical and neurophysiological data.

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Neurotrophic factors such as nerve growth factor (NGF) promote a wide variety of responses in neurons, including differentiation, survival, plasticity, and repair. Such actions often require changes in gene expression. To identify the regulated genes and thereby to more fully understand the NGF mechanism, we carried out serial analysis of gene expression (SAGE) profiling of transcripts derived from rat PC12 cells before and after NGF-promoted neuronal differentiation. Multiple criteria supported the reliability of the profile. Approximately 157,000 SAGE tags were analyzed, representing at least 21,000 unique transcripts. Of these, nearly 800 were regulated by 6-fold or more in response to NGF. Approximately 150 of the regulated transcripts have been matched to named genes, the majority of which were not previously known to be NGF-responsive. Functional categorization of the regulated genes provides insight into the complex, integrated mechanism by which NGF promotes its multiple actions. It is anticipated that as genomic sequence information accrues the data derived here will continue to provide information about neurotrophic factor mechanisms.

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Cover title.

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Exploratory factor analysis is a widely used statistical technique in the social sciences. It attempts to identify underlying factors that explain the pattern of correlations within a set of observed variables. A statistical software package is needed to perform the calcula- tions. However, there are some limitations with popular statistical software packages, like SPSS. The R programming language is a free software package for statistical and graphical computing. It o ers many packages written by contributors from all over the world and programming resources that allow it to overcome the dialog limitations of SPSS. This paper o ers an SPSS dialog written in the R programming language with the help of some packages, so that researchers with little or no knowledge in programming, or those who are accustomed to making their calculations based on statistical dialogs, have more options when applying factor analysis to their data and hence can adopt a better approach when dealing with ordinal, Likert-type data.

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The authors have standardized methods for evaluation of the activity of the glucose-6-phosphate dehydrogenase and of glutathione reductase. The general principle of the first method was based on methemoglobin formation by sodium nitrite followed by stimulation of the glucose-6-phosphate dehydrogenase with methylene blue. Forty six adults (23 males and 23 females) were studied. Subjects were not G6PD deficient and were aged 20 to 30 years. The results showed that methemoglobin reduction by methylene blue was 154.40 and 139.90 mg/min (p<0.05) for males and females, respectively, in whole blood, and 221.10 and 207.85 mg/min (n.s.), respectively, in washed red cells. These data showed that using washed red cells and 0.7g% sodium nitrite concentration produced no differences between sexes and also shortened reading time for the residual amount of methemoglobin to 90 minutes. Glutathione reductase activity was evaluated on the basis of the fact that cystamine (a thiol agent) binds to the SH groups of hemoglobin, forming complexes. These complexes are reversed by the action of glutathione reductase, with methemoglobin reduction occurring simultaneously with this reaction. Thirty two adults (16 males and 16 females) were studied. Subjects were not G6PD deficient and were aged 20 to 30 years. Methemoglobin reduction by cystamine was 81.27 and 91.13 mg/min (p<0.01) for males and females, respectively. These data showed that using washed red cells and 0.1 M cystamine concentration permits a reading of the residual amount of methemoglobin at 180 minutes of incubation. Glutathione reductase activity was evaluated by methemoglobin reduction by cystamine in 14 females before and after treatment with 10 mg riboflavin per day for 8 days. The results were 73.69 and 94.26 jug/min (p<0.01) before and after treatment, showing that riboflavin treatment increase glutathione reductase activity even in normal individuals. Three Black G6PD-deficient individuals (2 males and 1 female) were also studied. The G6PD and glutathione reductase were partially activated, the change being more intense in males. On the basis of race and of the laboratory characteristics observed, it is possible to suggest that the G6PD deficiency of these individuals is of the African type and that the female is heterozygous for this deficiency. Analysis of the results as a whole permitted us to conclude that the methods proposed here were efficient for evaluating the activity of the glucose-6-phosphate dehydrogenase and of glutathione reductase. The latter is dependent on the pentose pathway, which generates NADPH, and on riboflavin, a FAD precursor vitamin.