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At least 253 records · Page 14Linked to original sources
PubMed2006

AMDA: an R package for the automated microarray data analysis.

BACKGROUND: Microarrays are routinely used to assess mRNA transcript levels on a genome-wide scale. Large amount of microarray datasets are now available in several databases, and new experiments are constantly being performed. In spite of this fact, few and limited tools exist for quickly and easily analyzing the results. Microarray analysis can be challenging for researchers without the necessary training and it can be time-consuming for service providers with many users. RESULTS: To address these problems we have developed an automated microarray data analysis (AMDA) software, which provides scientists with an easy and integrated system for the analysis of Affymetrix microarray experiments. AMDA is free and it is available as an R package. It is based on the Bioconductor project that provides a number of powerful bioinformatics and microarray analysis tools. This automated pipeline integrates different functions available in the R and Bioconductor projects with newly developed functions. AMDA covers all of the steps, performing a full data analysis, including image analysis, quality controls, normalization, selection of differentially expressed genes, clustering, correspondence analysis and functional evaluation. Finally a LaTEX document is dynamically generated depending on the performed analysis steps. The generated report contains comments and analysis results as well as the references to several files for a deeper investigation. CONCLUSION: AMDA is freely available as an R package under the GPL license. The package as well as an example analysis report can be downloaded in the Services/Bioinformatics section of the Genopolis http://www.genopolis.it/.

Algorithms↗
PubMed1990

Area normalization of the renal region of interest in radionuclide renography data analysis: a misconception.

Relative renal function is estimated by comparing the area under the second segment of the curve from the renal region of interest in a renographic study. We have examined the problems arising out of area normalization of the renal region of interest in the data analysis for relative renal function evaluation. Error analysis by computer simulation proves that this method of data analysis is highly misleading and erroneous.

Humans↗
PubMed2003

Experimental validation of novel and conventional approaches to quantitative real-time PCR data analysis.

Real-time PCR is being used increasingly as the method of choice for mRNA quantification, allowing rapid analysis of gene expression from low quantities of starting template. Despite a wide range of approaches, the same principles underlie all data analysis, with standard approaches broadly classified as either absolute or relative. In this study we use a variety of absolute and relative approaches of data analysis to investigate nocturnal c-fos expression in wild-type and retinally degenerate mice. In addition, we apply a simple algorithm to calculate the amplification efficiency of every sample from its amplification profile. We confirm that nocturnal c-fos expression in the rodent eye originates from the photoreceptor layer, with around a 5-fold reduction in nocturnal c-fos expression in mice lacking rods and cones. Furthermore, we illustrate that differences in the results obtained from absolute and relative approaches are underpinned by differences in the calculated PCR efficiency. By calculating the amplification efficiency from the samples under analysis, comparable results may be obtained without the need for standard curves. We have automated this method to provide a means of streamlining the real-time PCR process, enabling analysis of experimental samples based upon their own reaction kinetics rather than those of artificial standards.

Actins↗
PubMed2006

Multivariate data analysis as a fast tool in evaluation of solid state phenomena.

A thorough understanding of solid state properties is of growing importance. It is often necessary to apply multiple techniques offering complementary information to fully understand the solid state behavior of a given compound and the relations between various polymorphic forms. The vast amount of information generated can be overwhelming and the need for more effective data analysis tools is well recognized. The aim of this study was to investigate the use of multivariate data analysis, in particular principal component analysis (PCA), for fast analysis of solid state information. The data sets analyzed covered dehydration phenomena of a set of hydrates followed by variable temperature X-ray powder diffractometry and Raman spectroscopy and the crystallization of amorphous lactose monitored by Raman spectroscopy. Identification of different transitional states upon the dehydration enabled the molecular level interpretation of the structural changes related to the loss of water, as well as interpretation of the phenomena related to the crystallization. The critical temperatures or critical time points were identified easily using the principal component analysis. The variables (diffraction angles or wavenumbers) that changed could be identified by the careful interpretation of the loadings plots. The PCA approach provides an effective tool for fast screening of solid state information.

Anti-Bacterial Agents↗
PubMed1990

Empirical considerations in orthopaedic research design and data analysis. Part II: The application of data analytic techniques.

To assure that a hypothesis is tested as rigorously as possible, the proper statistical method must be used to analyze the data. But without a strong background in statistics, it may be difficult to determine the efficacy of the data analytic technique used in the study. This paper describes several widely used data analytic techniques and offers examples of their proper application in orthopaedic research design.

Data Interpretation, Statistical↗
PubMed1994

Application of the exploratory data analysis for evaluating the toxicity of chlorinated phenol derivatives by various cell models.

Exploratory data analysis based on multivariate statistical analysis techniques was introduced as a new approach to expressing the toxicity of chemical substances at the simultaneous acceptance of various cell models. Using principal component analysis and cluster analysis methods the toxicity of chlorinated phenol derivatives on employing some of the cell models (chlorococcal algae, cyanobacteria, bacteria, micromycetes, plant and animal cells) was characterized. The previous empirical experience that the toxicity of chlorinated phenol derivatives will increase with a growing degree of chlorination and that the presence of the methoxy group will cause a lowering of the toxic effect was demonstrated. The relationship between groups of tests used was presented.

Allium↗
PubMed2005

[Cluster sampling: consequences of data analysis on drawing conclusions].

BACKGROUND: Cluster sampling is commonly used since it does not require a sampling frame which lists all the individual enumeration units. However, this sampling design is often less precise than simple random sampling due to frequent homogeneity of individuals within clusters. This note illustrates that the precision of parameters such as mean, prevalence and odds ratio can be biased when the data analysis ignores the sampling design, yielding to possibly erroneous conclusions. METHODS: Data from a cluster sampling among clandestine sex workers in Senegal were used. Two analyses were performed and their results were compared. The first analysis took into account the sampling design (design-based analysis) while the second did not (naïve analysis). RESULTS: The range of confidence intervals in design-based analysis differed from -43% to +84% with regard to those of naive analysis, and different conclusions could be drawn. For instance, the human immunodeficiency virus (HIV) infection in clandestine sex workers was associated with condoms use and perceived risk of HIV infection in design-based analysis but not in naive analysis. CONCLUSION: The data analysis must take into account the sampling design, and this is facilitated by the availability of statistical software with survey analysis capabilities.

Adult↗
PubMed2006

A new automated flow cytometry data analysis approach for the diagnostic screening of neoplastic B-cell disorders in peripheral blood samples with absolute lymphocytosis.

Currently, multiparameter flow cytometry immunophenotyping is the selected method for the differential diagnostic screening between reactive lymphocytosis and neoplastic B-cell chronic lymphoproliferative disorders (B-CLPD). Despite this, current multiparameter flow cytometry data analysis approaches still remain subjective due to the need of experienced personnel for both data analysis and interpretation of the results. In this study, we describe and validate a new automated method based on vector quantization algorithms to analyze multiparameter flow cytometry immunophenotyping data in a series of 307 peripheral blood (PB) samples. Our results show that the automated method of analysis proposed compares well with currently used manual approach and significantly improves semiautomated approaches and, that by using it, a highly efficient discrimination with 100% specificity and 100% sensitivity can be made between normal/reactive PB samples and cases with B-CLPD based on the total B-cell number and/or the sIgkappa+/sIglambda+ B-cell ratio. In addition, the method proved to be able to detect the presence of pathologic neoplastic B-cells even when these are present at low frequencies (<5% of all lymphocytes in the sample) and in poor-quality samples enriched in 'noise' events.

Artifacts↗
PubMed1983

A categorical data analysis of contacts with the Family Health Clinic, Calabar, Nigeria.

The relationships of population, environmental and accessibility variables to registration and attendance by mothers of children under 6 at the Family Health Clinic in Calabar, Nigeria are investigated. The technique used to analyze the data collected is categorical data analysis which proceeds in two stages, variable selection to reduce the variable set and fitting a log-linear model to the reduced set. Details of the statistical procedures used are provided to indicate how categorical data analysis can be used as a valuable tool of analysis in medical geographical studies that employ count or frequency data. It was found that younger mothers and Ibibio women registered more often at the clinic than did their counterparts. However, if the relatively sparse data on fathers is accepted, the association between age and registration is found to be spurious and a model can be substituted which shows younger fathers and fathers who spoke a non-Efik/Ibibio language to be associated with higher clinic registration of mothers. It was further found that for registered mothers the probability of a clinic visit was decreased by mother's age, increased by distance given no travel cost, unaffected by distance given some travel cost, increased by travel cost given a short distance to the clinic and decreased by travel cost given a longer distance from the clinic. These results are discussed in relation to population characteristics such as socio-economic status, clinic procedures such as health worker activities, transportation availability in Calabar, the spatial ecology of the city and local environmental conditions.

Adult↗
PubMed2006

An accurate and reliable method of thermal data analysis in thermal imaging of the anterior knee for use in cryotherapy research.

OBJECTIVE: To develop an anatomic marker system (AMS) as an accurate, reliable method of thermal imaging data analysis, for use in cryotherapy research. DESIGN: Investigation of the accuracy of new thermal imaging technique. SETTING: Hospital orthopedic outpatient department in England. PARTICIPANTS: Consecutive sample of 9 patients referred to anterior knee pain clinic. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Thermally inert markers were placed at specific anatomic locations, defining an area over the anterior knee of patients with anterior knee pain. A baseline thermal image was taken. Patients underwent a 3-minute thermal washout of the affected knee. Thermal images were collected at a rate of 1 image per minute for a 20-minute re-warming period. A Matlab (version 7.0) program was written to digitize the marker positions and subsequently calculate the mean of the area over the anterior knee. Virtual markers were then defined as 15% distal from the proximal marker, 30% proximal from the distal markers, 15% lateral from the medial marker, and 15% medial from the lateral marker. The virtual markers formed an ellipse, which defined an area representative of the patella shape. Within the ellipse, the mean value of the full pixels determined the mean temperature of this region. Ten raters were recruited to use the program and interrater reliability was investigated. RESULTS: The intraclass correlation coefficient produced coefficients within acceptable bounds, ranging from .82 to .97, indicating adequate interrater reliability. CONCLUSIONS: The AMS provides an accurate, reliable method for thermal imaging data analysis and is a reliable tool with which to advance cryotherapy research.

Analysis of Variance↗
PubMed2005

Intelligent Data Analysis of clinical trials.

We describe the software architecture of DART, an Intelligent Data-Analysis (IDA) tool for clinical trials data. This tool, which is coupled with COATI, a generic clinical trials database, embodies rule-based systems for data extraction and preparation, and algorithm-driven statistical analysis for the creation of fully ICH-compliant study reports.

Algorithms↗
PubMed2004

A flexible data analysis tool for chemical genetic screens.

High-throughput assays generate immense quantities of data that require sophisticated data analysis tools. We have created a freely available software tool, SLIMS (Small Laboratory Information Management System), for chemical genetics which facilitates the collection and analysis of large-scale chemical screening data. Compound structures, physical locations, and raw data can be loaded into SLIMS. Raw data from high-throughput assays are normalized using flexible analysis protocols, and systematic spatial errors are automatically identified and corrected. Various computational analyses are performed on tested compounds, and dilution-series data are processed using standard or user-defined algorithms. Finally, published literature associated with active compounds is automatically retrieved from Medline and processed to yield potential mechanisms of actions. SLIMS provides a framework for analyzing high-throughput assay data both as a laboratory information management system and as a platform for experimental analysis.

Cyclic AMP Response Element-Binding Protein↗
PubMed2003

[Neurocognition and PET. Strategies for data analysis in activation studies on working memory].

AIM: In cognitive neuroscience regional cerebral blood flow (rCBF) imaging with positron-emission-tomography (PET) is a powerful tool to characterize different aspects of cognitive processes by using different data analysis approaches. By use of an n-back verbal working memory task (varied from 0- to 3-back) we present cognitive subtraction analysis as basic strategy as well as parametric and covariance analyses and discuss the results. METHODS: Correlation analyses were performed using the individual performance rate as an external covariate, computing inter-regional correlations, and as network analysis applying structural equation modelling to evaluate the effective connectivity between the involved brain regions. RESULTS: Subtraction analyses revealed a fronto-parietal neuronal network also including the anterior cingulate cortex and the cerebellum. With higher memory load the parametric analysis evidenced linear rCBF increases in prefrontal, pre-motor and inferior parietal areas including the precuneus as well as in the anterior cingulate cortex. The rCBF correlation with the individual performance as external covariate depicted negative correlations in bilateral prefrontal and inferior parietal regions, in the precuneus and the anterior cingulate cortex. The network analysis demonstrated mainly occipito-frontally directed interactions which were predominantly left-hemispheric. Additionally, strong linkages were found between extrastriate and parietal regions as well as within the parietal cortex. CONCLUSION: The data analysis approaches presented here contribute to an extended and more elaborated understanding of cognitive processes and their different sub-aspects.

Brain↗
PubMed2004

A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume.

Atlas normalization, as commonly used by functional data analysis, provides an automated solution to the widely encountered problem of correcting for head size variation in regional and whole-brain morphometric analyses, so long as an age- and population-appropriate target atlas is used. In the present article, we develop and validate an atlas normalization procedure for head size correction using manual total intracranial volume (TIV) measurement as a reference. The target image used for atlas transformation consisted of a merged young and old-adult template specifically created for cross age-span normalization. Automated atlas transformation generated the Atlas Scaling Factor (ASF) defined as the volume-scaling factor required to match each individual to the atlas target. Because atlas normalization equates head size, the ASF should be proportional to TIV. A validation analysis was performed on 147 subjects to evaluate ASF as a proxy for manual TIV measurement. In addition, 19 subjects were imaged on multiple days to assess test-retest reliability. Results indicated that the ASF was (1) equivalent to manual TIV normalization (r = 0.93), (2) reliable across multiple imaging sessions (r = 1.00; mean absolute percentage of difference = 0.51%), (3) able to connect between-gender head size differences, and (4) minimally biased in demented older adults with marked atrophy. Hippocampal volume differences between nondemented (n = 49) and demented (n = 50) older adults (measured manually) were equivalent whether corrected using manual TIV or automated ASF (effect sizes of 1.29 and 1.46, respectively). To provide normative values, ASF was used to automatically derive estimated TIV (eTIV) in 335 subjects aged 15-96 including both clinically characterized nondemented (n = 77) and demented (n = 90) older adults. Differences in eTIV between nondemented and demented groups were negligible, thus failing to support the hypothesis that large premorbid brain size moderates Alzheimer's disease. Gender was the only robust factor that influenced eTIV. Men showed an approximately approximately 12% larger eTIV than women. These results demonstrate that atlas normalization using appropriate template images provides a robust, automated method for head size correction that is equivalent to manual TIV correction in studies of aging and dementia. Thus, atlas normalization provides a common framework for both morphometric and functional data analysis.

Adolescent↗
PubMed2003

Short tandem repeat data analysis in a Mongolian population.

Fifteen somatic (D8S1179, D21S11, D7S820, CSF1PO, D3S1358, TH01, D13S317, D16S539, D2S1338, D19S433, VWA, TPOX, D18S51, D5S818, FGA) and five Y-chromosome (DYS19, DYS390, DYS391, DYS392, DYS393) short tandem repeat (STR) system analyses were carried out in a Mongolian population in order to define the possible relationship between Mongolians and old Hungarian population. For STR data analysis the Microsoft Excel-PowerStats program was used. Inter-population data analysis was performed with Arlequin Software ver. 2.000. The somatic markers showed meaningful difference between Mongolians and old Hungarians but the distribution of the Y-chromosome STR systems refers to a closer relationship between the old Hungarian and oriental populations.

Chromosomes, Human, Y↗
PubMed2006

Reanalysis of the Grønnerød (2003) Rorschach temporal stability meta-analysis data set.

I reanalyzed the Grønnerød (2003) Rorschach temporal stability meta-analysis data with a theoretically driven hierarchical regression analysis. I also examined the intrarater reliability of initial coding decisions and verified their consistency. In the new regression analyses, retest period strengthened its influence on stability, whereas methodological factors showed a tendency toward influence. The new results are more in line with the results from Grønnerød's (2004) psychotherapy change meta-analysis results.

Humans↗
PubMed2006

Novel methods of quantitative real-time PCR data analysis in a murine Helicobacter pylori vaccine model.

Monitoring of Helicobacter pylori in the stomach is important to assess the efficacy of new vaccines against the pathogen. To realise the full potential of quantitative real-time PCR (q-PCR), this technology has to offer accurate and easy models of post-PCR data analysis. In this work, we used a variety of absolute and relative approaches of q-PCR data analysis to monitor the H. pylori infection in the stomach of immunized mice. Relative quantification was performed with Ct-based methods, with the DART program, and with two methods based on the mathematical analysis of raw fluorescence kinetics, the LinReg program and the Sigmoidal Curve Fitting Method. The different calculation methods were validated in mice immunized with cell lysates of Lactococcus lactis expressing the H. pylori urease subunit B in combination with cholera toxin. The H. pylori load was found to be reduced in immunized mice by a factor of 50-144, depending on the calculation method employed. We found that relative quantification using DART, LinReg and Sigmoidal Curve Fitting methods generated similar results (infection ratios of 54-58) with absolute quantification results (54-65). Results were very different to those using relative quantification Ct-based methods without a correction for PCR efficiency (ratio of 92-144) and with results based on conventional culture method (ratio of 34). Overall, this study demonstrates that q-PCR associated with a relative quantification analysis is a powerful tool for the monitoring of microorganisms in tissue. It could be used as an alternative to standard curve approach especially for the investigation of microbial load in vaccine models.

Animals↗