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PubMed1987

Computer analysis of automated Edman degradation and amino acid analysis data.

Computer programs are described that allow facile analysis of data from a protein sequencer and amino acid analyzer. The sequencer program provides automated sequence interpretation while requiring minimal user interaction. The program serves as a powerful aid in deciphering mixture sequences and allows routine monitoring of sequencer performance. The computer program for amino acid analysis data provides the following calculations: mole percent, protein concentration and residues per mole with comparison between theoretical and calculated values. A plot of molecular weight versus deviation from integer values is calculated providing a measure of peptide or protein purity.

Amino Acids↗
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↗
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↗
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↗
PubMed1993

Data analysis in behavioral cerebral blood flow activation studies using xenon-133 clearance.

BACKGROUND AND PURPOSE: Three mainstream strategies exist to detect the responses of regional cerebral blood flow to functional activation. We tested the significance of changes in raw regional cerebral blood flow data, regional cerebral blood flow data normalized by division by global cerebral blood flow (dependent model of the regional-to-global cerebral blood flow relation), and regional cerebral blood flow data treating global cerebral blood flow as a covariate (independent model). Both latter models attempt to enhance regional sensitivity by removing global effects. We examined the sensitivity and pitfalls of these three strategies in behavioral activation studies. METHODS: These three strategies of data analysis were applied to changes in regional cerebral blood flow induced by a visuospatial problem-solving task in 38 healthy subjects as measured by the intravenous xenon-133 method with 32 stationary detectors. RESULTS: Mental activation increased blood flow in all regions of interest. Raw data were most sensitive and reliable to detect responses to mental stimulation. Both the independent and dependent models to remove global effects were less sensitive and falsely indicated deactivation in regions that were clearly stimulated. CONCLUSIONS: In behavioral activation paradigms, safe data analysis should be restricted to using raw regional cerebral blood flow increases without normalization or separation of global from regional effects. Studies using complex stimulation tasks should be scrutinized for global cerebral blood flow effects confounding regional responses.

Behavior↗
PubMed1994

A visual data analysis system for the medical image processing.

We developed a visual data analysis system that can easily manage a large volume of medical imaging data. This system can analyze sets of imaging data using general image processing methods, so that various kinds of medical imaging data such as ECG charts, X ray image films, and MRI images, can be processed. The system has a graphical user interface (GUI). A physician who is novice at the system can manipulate the imaging data intuitively by pull down menus, pop up menus and buttons within the window system. The system can run on a standard UNIX workstation which is faster and more powerful than most personal computers. The system needs an X window system/Motif and C compiler. These are standard system programs already available on most UNIX workstations. The source code of the system can be retrieved from our anonymous ftp site via Internet.

Computer Graphics↗
PubMed2025

Augmented kurtosis-based projection pursuit: a novel, advanced machine learning approach for multi-omics data analysis and integration.

Due to the heterogeneity of multi-omics data, exacting their maximum information potential remains a challenge. Whereas some solutions have been offered, most cannot overcome the large linear dynamic range associated with such data, while others require large biological effect sizes to produce meaningful models. Here, we (i) perform a comprehensive benchmarking of multi-omics data analysis tools, and (ii) introduce kurtosis-based projection pursuit analysis, augmented with classification and regression trees (kPPA-CART) as a robust, easy-to-implement alternative. Using ground truth data, we demonstrate that kPPA-CART exhibits superiority in inferring biological significance from low-intensity (low-count) features and studies with small biological effect sizes. Applying it to experimental breast cancer data from The Cancer Genome Atlas, we identify novel genes that cluster the samples into subtypes that mimic the canonical PAM50 classes with notable improvements. Validating with external metastatic breast cancer data from the AURORA US consortium, kPPA-CART identifies genes that are associated with poor event-free survival and additional clustering associated with increased tumor mutational burden. Finally, we provide an R package and an online implementation of kPPA-CART.

Humans↗
PubMed1993

Estimating fertility potential via semen analysis data.

The aim of this study was to evaluate diagnostic profiles for the assessment of semen analysis data with respect to male fertility potential. Semen samples taken from 208 patients of known fertility and suspected infertility were studied by conventional semen analysis methods. The data throw doubt upon the validity of an approach based on the number of deviations from the normal standard values defined by the World Health Organization. The alternative approach of a specific semen characteristic (particularly morphology) as the major predictor of fertility produced no beneficial results. However, the semen analysis index based on semen volume, sperm count, percentage motility and normal forms resulted in a high accuracy of classification but for only 44% of the cases, with 3% false negatives and 10% false positives using cut-off indices of > or = 0.6 and < or = -1.0 for defining 'fertile' and 'infertile' zones, respectively. In conclusion, it is emphasized that there are a number of specific semen analysis variables, each expressing a different aspect of male fertility potential which, when combined in correct proportion, do provide the optimal evaluation of the male fertility status. However, in order to increase the prognostic potential of the semen sample, new and meaningful parameters must be discovered.

Adult↗
PubMed1987

Novel data analysis for synchronised spontaneous neuromagnetic activity.

A novel approach to neuromagnetic data analysis is presented. This technique is aimed at studying synchronised spontaneous activity (SSA) and has been used to resolve two different signals from one single evoked response, providing evidence for two possibly distinct sources. The data presented are consistent with a model that permits the generators of spontaneous activity to be synchronised by sensory stimuli.

Brain↗
PubMed2025

A hierarchical, count-based model highlights challenges in scATAC-seq data analysis and points to opportunities to extract finer-resolution information.

BACKGROUND: Data from Single-cell Assay for Transposase Accessible Chromatin with Sequencing (scATAC-seq) is highly sparse. While current computational methods feature a range of transformation procedures to extract meaningful information, major challenges remain. RESULTS: Here, we discuss the major scATAC-seq data analysis challenges such as sequencing depth normalization and region-specific biases. We present a hierarchical count model that is motivated by the data generating process of scATAC-seq data. Our simulations show that current scATAC-seq data, while clearly containing physical single-cell resolution, are too sparse to infer true informational-level single-cell, single-region of chromatin accessibility states. CONCLUSIONS: While the broad utility of scATAC-seq at a cell type level is undeniable, describing it as fully resolving chromatin accessibility at single-cell resolution, particularly at individual locus level, may overstate the level of detail currently achievable. We conclude that chromatin accessibility profiling at true single-cell, single-region resolution is challenging with current data sensitivity, but that it may be achieved with promising developments in optimizing the efficiency of scATAC-seq assays.

Single-Cell Analysis↗
PubMedDate not supplied

[Computer-assisted data analysis in a pediatric intensive care unit].

Computer assisted real time data analysis introduces a reasonable method of judgment into patient monitoring systems. From fast changing vital parameters discrete heart and respiration rate samples are immediately evaluated and presented as graphs near the bedside. Thus, statistical routines can increase the better understanding of instable clinical conditions and lend support to the decision making process. The early detection of a pathological trend in a patient whose ability to compensate is still present provides necessary time for diagnostic or preventive countermeasures in case of emergency.

Computers↗
PubMed1993

An evaluation of five commercial immunoassay data analysis software systems.

An evaluation of five commercial software systems used for immunoassay data analysis revealed numerous deficiencies. Often, the utility of statistical output was compromised by poor documentation. Several data sets were run through each system using a four-parameter calibration function, and the results were compared to those from an independent method. Comparable results between systems were obtained, but often several attempts at analysis were necessary. The evaluation process revealed that it is difficult to monitor the numerous options available on these types of programs, and that incorrect results could easily be obtained if comparison analyses were not used. Recommendations for improved software functionality and for using the four-parameter calibration model are presented.

Data Interpretation, Statistical↗
PubMed1993

Exploratory data analysis of hyperlipidemia on the Macintosh: software tools for analysis of biochemical, clinical, and genetic variables in 1677 consecutive lipid clinic patients.

Exploratory data analysis (EDA) software facilitates unstructured, iterative open exploration of complex datasets with the aid of multiple linked graphical displays. We are investigating relationships between plasma lipoproteins and coronary artery disease by retrospective analysis of 1677 consecutive UCSF Lipid Clinic patients. Our preliminary experience is with Data Deck 3.0 although several additional software programs (JMP 2.0, Systat 5.1, Minitab 8.0, StatView 4.0) are mentioned. Lipid diagnosis (751 women and 925 men) was 22% primary hypercholesterolemia, 19% combined hyperlipidemia, 3% dysbetalipoproteinemia, 15% endogenous lipemia, 4% mixed lipemia, 5% elevated Lp(a) and 32% with no major lipid abnormality. We found the Macintosh platform (68030) to be flexible and powerful for analysis of moderate size (less than 1 Mb) clinical datasets. High resolution color monitors (1024 x 768 pixels), fast hard disks (< 18 msec) and moderate amounts of system memory (8 + Mb) facilitate exploratory analysis.

Artificial Intelligence↗
PubMed1987

Histopathological criteria for progressive dementia disorders: clinical-pathological correlation and classification by multivariate data analysis.

Autopsied brains from 55 patients with dementia between 59-95 years of age (mean age 77.9 +/- 8.1 years) and 19 non-demented individuals between 46-91 years of age (mean age 74.3 +/- 10.5 years) were examined to establish histopathological criteria for normal ageing, primary degenerative [Alzheimer's disease (AD)/senile dementia of Alzheimer type (SDAT)] and vascular (multi-infarct) dementia (MID) disorders. Senile/neuritic plaques, neurofibrillary tangles, microscopic infarcts and perivascular serum protein deposits were quantified in the frontal lobe (Brodmann area 10) and in the hippocampus. The demented patients were classified according to the DSM-III criteria into AD/SDAT and MID. Operationally defined histopathological criteria for dementias, based on the degree/amount of the histopathological changes seen in aged non-demented patients, were postulated. The demented patients were clearly separable into three histopathological types, namely AD/SDAT, MID and AD-MID, the dementia type where both the degenerative and the vascular changes are coexistent in greater extent than are seen in the non-demented individuals. Using general clinical, gross neuroanatomical and histopathological data three separate dementia classes, namely AD/SDAT, MID and AD-MID, were visualized in two-dimensional space by multivariate data analysis. This analysis revealed that the pathology in the AD-MID patients was not merely a linear combination of the pathology in AD/SDAT and MID, indicating that AD-MID might represent a dementia type of its own. The clinical diagnosis for AD/SDAT and MID was certain in only half of the AD/SDAT and one third of the MID cases when evaluated histopathologically and by multivariate data analysis. AD/SDAT, MID and AD-MID were histopathologically diagnosed in 49%, 24% and 27%, respectively, of all the dementia cases studied. Opposite correlation between the number of tangles, plaques and the patient age in non-demented and AD/SDAT cases were observed, indicating that the pathogenesis of tangles and plaques in the two groups of patients might be different and that AD/SDAT might not be a form of an exaggerated ageing process.

Aged↗
PubMed1989

[The effect of smoking habit on aortic pulse wave velocity using a new method for data analysis].

We measured aortic pulse wave velocity (PWV) in 168 male adult cases of various arteriosclerotic diseases. In order to evaluate the effects of age, smoking habits, alcohol intake, and blood pressure, we applied the least median of squares (LMS) regression which was considered to be very useful for data analysis. The results showed that PWV level increased with age. Furthermore smoking was associated with increasing PWV level and this effect was also related to age. We concluded that the PWV was valuable as an index of arteriosclerosis, and instead of the classical least squares method, LMS regression was very useful for analysis of medical data.

Adult↗
PubMed1993

Diagnostic accuracy of pancreatic enzymes evaluated by use of multivariate data analysis.

We analyzed pancreatic enzyme data from 508 patients with suspected pancreatitis by neural network analysis, by an Expert multirule generation protocol, and by receiver-operator characteristic (ROC) curve analysis of a single test result. Neural network analysis showed that use of lipase provided the best means for diagnosing pancreatitis. Diagnostic accuracies achieved by using amylase only, lipase only, and amylase and lipase in combination were 76%, 82%, and 84%, respectively. Use of the Expert rule generation protocol provided a diagnostic accuracy of 92% when rules for single and multiple samplings were combined. ROC curve analysis for initial enzyme activities showed the maximal diagnostic accuracy to be 82% and 85% for amylase and lipase, respectively; use of peak enzyme activities yielded accuracies of 81% and 88%, respectively. The evaluation of laboratory test data should include analysis of the diagnostic accuracy of laboratory tests by multivariate techniques such as neural network analysis or an Expert systems approach. Multivariate analysis should allow for a more realistic assessment of the diagnosis accuracy of laboratory tests because all the available data are included in the evaluation.

Amylases↗