Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Data Analysis”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11Linked to original sources

From patterns to pathways: gene expression data analysis comes of age.

Many different biological questions are routinely studied using transcriptional profiling on microarrays. A wide range of approaches are available for gleaning insights from the data obtained from such experiments. The appropriate choice of data-analysis technique depends both on the data and on the goals of the experiment. This review summarizes some of the common themes in microarray data analysis, including detection of differential expression, clustering, and predicting sample characteristics. Several approaches to each problem, and their relative merits, are discussed and key areas for additional research highlighted.

Cluster Analysis↗

Challenges and opportunities in proteomics data analysis.

Accurate, consistent, and transparent data processing and analysis are integral and critical parts of proteomics workflows in general and for biomarker discovery in particular. Definition of common standards for data representation and analysis and the creation of data repositories are essential to compare, exchange, and share data within the community. Current issues in data processing, analysis, and validation are discussed together with opportunities for improving the process in the future and for defining alternative workflows.

Databases, Protein↗

Establishing student competency in qualitative research: can undergraduate nursing students perform qualitative data analysis?

Many undergraduate nursing programs require some level of research competency of their graduates. However, the competency level may vary depending on program goals and often is focused on quantitative methodologies. The purpose of this research was to determine nursing students' ability to perform qualitative data analysis. Twenty-eight undergraduate students enrolled in a data analysis course in the junior year of their baccalaureate program participated. After selecting the research question, students collected interview data from each other and posted it using a Web-based program. The students and instructor then performed a content analysis. After reviewing the instructor's analysis, which revealed three core themes, students' written analyses were read to determine their congruence with the instructor-generated themes. There was 89% agreement on the first theme, 96% agreement on the second theme, and 61% agreement on the third theme. Because of the high agreement rates between the instructor and student analyses, the author concluded that undergraduate nursing students, when provided with appropriate instruction, are capable of performing qualitative data analysis.

Adult↗

Are standardized mortality ratios valid for public health data analysis?

Standardized mortality ratios (SMRs) have been criticized as lacking validity, and it has been recommended to use standardized rate ratios (SRRs) instead. A review of the epidemiology literature and standard epidemiology textbooks showed disagreement concerning the validity of SMRs and a lack of data to support claims concerning their validity. Therefore, we sought to determine the validity of SMRs in public health data analysis. Simulations were carried out using widely disparate study population age distributions and disease rates encountered in public health data analysis. We compared SMRs and SRRs as absolute measures of increased mortality in a population, and for ranking mortality in different populations. The simulations showed that SMRs changed by 6 per cent to 8 per cent when the age distribution was changed from that of a 'young' age distribution to that of an 'old' age distribution. In comparison, SRRs changed by 4 per cent to 5 per cent when the age-adjustment standard was changed from the 1940 U.S. Census population to the 1990 U.S. Census population. County rankings by SRR were somewhat more similar among themselves than when compared with rankings by SMR, but the differences were not large. Based on our findings, SMRs are of similar usefulness to SRRs in public health data analysis, will lead to similar conclusions, and may be used to compare different geographic areas.

Adolescent↗

Systematic reviews of bladder training and voiding programmes in adults: a synopsis of findings from data analysis and outcomes using metastudy techniques.

AIM: This paper reports a comparison of the data analysis and outcomes from four Cochrane systematic reviews on bladder training and voiding programmes for the management of urinary incontinence using metastudy descriptive techniques to inform clinical practice, generate new ideas and identify future research directions. BACKGROUND: Bladder training is used for cognitively and physically able adults to regain continence by increasing the time interval between voids. Prompted voiding, habit retraining and timed voiding, collectively known as voiding programmes, are generally used for people with cognitive and physical impairments in institutional settings. Bladder training and voiding programmes feature as common clinical practice for the management of urinary incontinence. METHODS: A synopsis of four Cochrane systematic reviews that included randomized controlled trials on bladder training, prompted voiding, habit retraining and timed voiding was undertaken using metastudy techniques for the synthesis of qualitative research, and has provided a discursive comparison and contrast of the meta-data analysis and outcomes of these reviews. RESULTS: Frequency of incontinence was the most common and constant outcome measure of effectiveness in the reviews. Limited data were available on other health outcomes, change in dependency status, quality of life and cost-effectiveness. The systematic review on bladder training included different types of urinary incontinence, whereas those on voiding programmes did not differentiate the type of incontinence. There is evidence on the effectiveness of bladder training but long-term follow up studies are needed. Evidence on the effectiveness of voiding programmes is limited and not available for many outcomes. CONCLUSION: Future research needs to consider the theory underpinning interventions for bladder training and voiding programmes for urinary incontinence and should incorporate recognized 'quality' research designs, established outcomes and long-term follow up. It is unclear whether health outcomes for people with comorbidities, cognitive and physical impairments will improve if extensive diagnostic and assessment investigations are undertaken.

Adult↗

Computer-assisted diagnosis by a model-free system of direct data analysis.

The basis of the method of data analysis presented is, in the case of any diagnostic test, the automatic compilation of separate frequency distributions for each diagnostic classification. The distinction of different test results for different diseases (the correlation for which the tests are used) can thus be quantitatively monitored. This offers opportunities for more specific control of the accuracy of the data base. Measurements of relative frequencies obtained from the frequency distributions of individuals with and without a given disease can serve as a quantitative handle for the selection of the combination of tests, and for adjustments of individual parameters, which will maximize the discrimination. The usual cutoffs are not used. A data-processing system can serve for the direct incorporation of patient chart data (including test results), and for the automation of the analysis described, with pattern recognition or cluster-seeking techniques. The ability of this system of analysis to minimize some of the problems associated with methods utilizing mathematical models is discussed.

Diagnosis, Computer-Assisted↗

Longitudinal data analysis (repeated measures) in clinical trials.

Longitudinal data is often collected in clinical trials to examine the effect of treatment on the disease process over time. This paper reviews and summarizes much of the methodological research on longitudinal data analysis from the perspective of clinical trials. We discuss methodology for analysing Gaussian and discrete longitudinal data and show how these methods can be applied to clinical trials data. We illustrate these methods with five examples of clinical trials with longitudinal outcomes. We also discuss issues of particular concern in clinical trials including sequential monitoring and adjustments for missing data. A review of current software for analysing longitudinal data is also provided. Published in 1999 by John Wiley & Sons, Ltd. This article is a US Government work and is the public domain in the United States.

Clinical Trials as Topic↗

An investigation of the use of the Hedin-Lundqvist exchange and correlation potential in EXAFS data analysis.

In real systems, inelastic processes remove photoelectrons from the elastic scattering channel. This reduces the amplitude of the EXAFS. Traditionally the discrepancies between experimental and theoretical amplitudes were treated by including two semi-empirical reduction factors in the data analysis. Some inelastic effects may, however, be modelled more rigorously using a complex exchange and correlation potential, for example the Hedin-Lundqvist (HL) potential used in most EXAFS data-analysis programs. In this paper a systematic study of the effects of the HL potential on the calculated EXAFS amplitudes is presented. Expressions are derived whereby the EXAFS amplitudes may be examined in the presence of an arbitrary complex potential independently to the rest of the EXAFS signal. These results are used to study the effects of the HL potential on EXAFS data analysis in detail.

Journal Article↗

Microcomputer-assisted univariate survival data analysis using Kaplan-Meier life table estimators.

We describe a microcomputer program (KMSURV) for exploratory univariate statistical analysis of survival data which is directly applicable to the evaluation of clinical trials and to retrospective epidemiological studies of hospital registry-based data. The program calculates life-table-like information based on Kaplan-Meier's product-limit estimators of the survivorship function S(t) and provides summary measures of average survival times. In addition, two non-parametric tests for the comparison of survival distributions are performed. A report-quality, high resolution plot of the S(t) estimates for all groups being compared complements each set of analyses. KMSURV is not a simple adaptation of a mainframe statistical analysis package and, thus, it utilizes efficiently the interactive environment which is inherent in microcomputing.

Actuarial Analysis↗

Clustering algorithms and other exploratory methods for microarray data analysis.

OBJECTIVES: We introduce methods for the exploratory analysis of microarray data, especially focusing on cluster algorithms. Benefits and problems are discussed. METHODS: We describe application and suitability of unsupervised learning methods for the classification of gene expression data. Cluster algorithms are treated in more detail, including assessment of cluster quality. RESULTS: When dealing with microarray data, most cluster algorithms must be applied with caution. As long as the structure of the true generating models of such data is not fully understood, the use of simple algorithms seems to be more appropriate than the application of complex black-box algorithms. New methods explicitly targeted to the analysis of microarray data are increasingly being developed in order to increase the amount of useful information extracted from the experiments. CONCLUSIONS: Unsupervised methods can be a helpful tool for the analysis of microarray data, but a critical choice of the algorithm and a careful interpretation of the results are required in order to avoid false conclusions.

Algorithms↗

Exploratory data analysis reveals visuovisual interhemispheric transfer in functional magnetic resonance imaging.

We used an exploratory data analysis approach to detect interhemispheric processing of complex visual stimuli in functional magnetic resonance imaging (fMRI). A crossed-uncrossed visual field paradigm was used to elicit interhemispheric transfer of picture/word information. Under the uncrossed (control) condition, the stimuli were presented to the preferential hemispheres (pictures to the left visual field/right hemisphere and words to the right visual field/left hemisphere). Under the crossed condition, the visual field presentation was switched in order to elicit increased interhemispheric processing. Fuzzy cluster analysis revealed significantly more crossed activity in cortical areas near the splenium of the corpus callosum. As expected, examination of the activation revealed smaller responses in perisplenial regions (relative to visual responses in the medial extrastriate regions). The exploratory results were compared with those obtained from parametric and masked analyses. The findings confirm that fMRI can be used to detect interhemispheric transfer of picture/word information. The activation was optimally characterized using exploratory data analysis.

Adult↗

Reduction of interlaboratory variability in flow cytometric immunophenotyping by standardization of instrument set-up and calibration, and standard list mode data analysis.

Two workshops addressed the question to which degree standardization of instrument set-up and calibration, and standard list mode data analysis would reduce interlaboratory variability of flow cytometric results on prestained peripheral blood mononuclear cells (PBMC). Standard instrument set-up included uniform positioning of the "windows of analysis" for the forward and sideward light scatter and fluorescence (FL) 1 (i.e., fluorescein isothiocyanate [FITC]) and 2 (i.e., phycoerythrin [PE]) parameters. Reference standards and PBMC, double-stained with FITC- and PE-conjugated monoclonal antibodies covering a wide range of FL intensities and coexpression patterns, were sent out to 25 laboratories in Workshop 1 and to 35 laboratories in Workshop 2 with the following requests: a) to set up instruments according to local and standard protocols, b) to acquire list mode data on the PBMC with both instrument settings, and c) to analyze both datasets according to local protocols. Standard analysis of the list mode data acquired with uniform instrument settings was performed centrally using so-called "latent class model" software (Van Putten et al., Cytometry 14:86-96, 1993). This software provides an automated, "no-gating" analytical method of lymphocyte immunophenotypes and employs fixed FL marker settings as defined prior to each analytical run. In Workshop 1, these markers were set in identical histogram channels for all instruments based on results obtained with a reference instrument. Standard analysis of list mode data acquired after uniform instrument set-up led only to a 13% reduction of interlaboratory variability of results as compared to data analysis using local protocols. The standard protocol for instrument set-up led to uniform positioning of relatively strong FL signals but variable positioning of unstained cells on the FL histogram scales. Hence, standard FL marker settings were inappropriate for some instruments. Therefore, instrument responses to FITC and PE signals in Workshop 2 were calibrated using microbeads labeled with FITC or PE in a range of predefined FL intensities expressed in MESF units (molecules of equivalent soluble fluorochrome). That approach allowed the positioning of the FL markers for the standard analysis on the basis of identical FL1 and FL2 intensities, expressed in MESF units, for all instruments. Standard analysis of list mode data acquired after uniform instrument set-up and calibrated FL marker settings led to a 43% reduction of interlaboratory variability as compared to data analysis to local protocols. We conclude that standard list mode data analysis using fixed FL marker settings reduces the interlaboratory variability of flow cytometric results on prestained PBMC, provided that the instruments have been set up in a uniform way and that FL markers have been standardized on the basis of calibration of each instrument's response to the corresponding FL signals.

Antigens, CD↗

Toward a computer assisted analysis of NOESY spectra: a multivariate data analysis of an RNA NOESY spectrum.

A multivariate data-representation of a portion of the H-NOESY spectrum of an RNA octamer duplex was used to explore the possibility of using Principal Component Analysis and Partial Least Squares Discrimination for pattern recognition. In this case, it is found that the methods can: (i) distinguish slices containing signal from those containing only noise, (ii) locate slices containing overlapping signals, and (iii) in some cases to segregate slices with unique aspects such as those from terminal nucleotides, overlapping signals, purine-H8, pyrimidine-H6 and adenine-H2 containing slices. These properties can easily be included in a scheme to automate spectral analysis. The formulation described here does not distinguish patterns needed to automate sequential assignment of resonances in NOESY spectra of RNA.

Base Sequence↗

DAMBE: software package for data analysis in molecular biology and evolution.

DAMBE (data analysis in molecular biology and evolution) is an integrated software package for converting, manipulating, statistically and graphically describing, and analyzing molecular sequence data with a user-friendly Windows 95/98/2000/NT interface. DAMBE is free and can be downloaded from http://web.hku.hk/~xxia/software/software.htm. The current version is 4.0.36.

Biological Evolution↗

DeeDeeExperiment: building an infrastructure for integrating and managing omics data analysis results in R/Bioconductor.

SUMMARY: Modern omics experiments now involve multiple conditions and complex designs, producing an increasingly large set of differential expression and functional enrichment analysis results. However, no standardized data structure exists to store and contextualize these results together with their metadata, leaving researchers with an unmanageable and potentially non-reproducible collection of results that are difficult to navigate and/or share. Here we introduce DeeDeeExperiment, a new S4 class for managing and storing omics data analysis results, implemented within the Bioconductor ecosystem, which promotes interoperability, reproducibility and good documentation. This class extends the widely used SingleCellExperiment object by introducing dedicated slots for Differential Expression (DEA) and Functional Enrichment Analysis (FEA) results, allowing users to organize, store, and retrieve information on multiple contrasts and associated metadata within a single data object, ultimately streamlining the management and interpretation of many omics datasets. AVAILABILITY AND IMPLEMENTATION: DeeDeeExperiment is available on Bioconductor under the MIT license (https://bioconductor.org/packages/DeeDeeExperiment), with its development version also available on Github (https://github.com/imbeimainz/DeeDeeExperiment).

Software↗

Child survivorship estimation: methods and data analysis.

"The past 20 years have seen extensive elaboration, refinement, and application of the original Brass method for estimating infant and child mortality from child survivorship data. This experience has confirmed the overall usefulness of the methods beyond question, but it has also shown that...estimates must be analyzed in relation to other relevant information before useful conclusions about the level and trend of mortality can be drawn.... This article aims to illustrate the importance of data analysis through a series of examples, including data for the Eastern Malaysian state of Sarawak, Mexico, Thailand, and Indonesia. Specific maneuvers include plotting completed parity distributions and 'time-plotting' mean numbers of children ever born from successive censuses. A substantive conclusion of general interest is that data for older women are not so widely defective as generally supposed."

Americas↗

WebArray: an online platform for microarray data analysis.

BACKGROUND: Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments. RESULTS: The currently implemented functions were based on limma and affy package from Bioconductor, the spacings LOESS histogram (SPLOSH) method, PCA-assisted normalization method and genome mapping method. WebArray incorporates these packages and provides a user-friendly interface for accessing a wide range of key functions of limma and others, such as spot quality weight, background correction, graphical plotting, normalization, linear modeling, empirical bayes statistical analysis, false discovery rate (FDR) estimation, chromosomal mapping for genome comparison. CONCLUSION: WebArray offers a convenient platform for bench biologists to access several cutting-edge microarray data analysis tools. The website is freely available at http://bioinformatics.skcc.org/webarray/. It runs on a Linux server with Apache and MySQL.

Algorithms↗

Gender differences in three dimensional gait analysis data from 98 healthy Korean adults.

OBJECTIVES: The research hypothesis was that healthy adults would walk differently according to their gender when walked barefoot at their comfortable speed. The aim of this study was to prove the hypothesis in healthy Korean adults. DESIGN: Between-gender statistical comparisons of the gait analysis data including spatiotemporal, three-dimensional joint kinematic and kinetic data. BACKGROUND: There have been few attempts to identify the significant gender differences in gait pattern and to explore their possible causes. METHODS: Healthy 98 Korean adults (47 females and 51 males) volunteered. Gait analysis data was obtained with opto-electric system and force plates. Normalization was used to avoid the body size effect. Gender difference was tested with independent t-test, ancova, and two-way repeated anova. RESULTS: Females were shorter, both in height and leg length ( P < 0.05 ). The cadence and pelvic width were as great as in males. They walked slower than males due to shorter stride length ( P < 0.05 ). The females had still shorter stride length and narrower step width ( P < 0.05 ), and they walked as fast as the males. Females walked with their pelvis tilted more anteriorly and more up and down oblique motion, hip joints more flexed-adducted-internally rotated, knee joint in more valgus angles ( P = 0.05 ). CONCLUSIONS: The gait analysis data had significant gender differences. We assume that the difference is due to gender features of the gait-related anatomy and habits. Comparison with other research shows some evidence for racial differences.

Adult↗