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Implementing a training resource for large-scale genomic data analysis in the All of Us Researcher Workbench.

A lack of representation in genomic research and limited access to computational training create barriers for many researchers seeking to analyze large-scale genetic datasets. The All of Us Research Program provides an unprecedented opportunity to address these gaps by offering genomic data from a broad range of participants, but its impact depends on equipping researchers with the necessary skills to use it effectively. The All of Us Biomedical Researcher (BR) Scholars Program at Baylor College of Medicine aims to break down these barriers by providing early-career researchers with hands-on training in computational genomics through the All of Us Evenings with Genetics Research Program. The year-long program begins with the faculty summit, an in-person computational boot camp that introduces scholars to foundational skills for using the All of Us dataset via a cloud-based research environment. The genomics tutorials focus on genome-wide association studies (GWASs), utilizing Jupyter Notebooks and the Hail computing framework to provide an accessible and scalable approach to large-scale data analysis. Scholars engage in hands-on exercises covering data preparation, quality control, association testing, and result interpretation. By the end of the summit, participants will have successfully conducted a GWAS, visualized key findings, and gained confidence in computational resource management. This initiative expands access to genomic research by equipping early-career researchers from a variety of backgrounds with the tools and knowledge to analyze All of Us data. By lowering barriers to entry and promoting the study of representative populations, the program fosters innovation in precision medicine and advances equity in genomic research.

Humans

Proficiency of the Tradescantia-micronucleus image analysis system for scoring micronucleus frequencies and data analysis.

The Tradescantia-micronucleus (Trad-MCN) bioassay is an efficient short-term test for genotoxicity of pollutants. In order to increase the efficiency and to standardize the micronucleus (MCN) scoring process, an automated scoring system was developed using the principle of image analysis in computer science. This assemblage is called the Tradescantia-micronucleus image analysis (Trad-MCNIA) system. The MCN frequencies scored by this system were compared with those scored by human observation for its proficiency. A set of low MCN frequency (around 5 MCN/100 tetrads) slides prepared from a control group, a set of medium MCN frequency (around 20 MCN/100 tetrads) slides prepared from sodium azide treated plant cuttings and a set of high MCN frequency (around 50 MCN/100 tetrads) slides prepared from X-ray treated materials were used for this study. In the low MCN frequency slides, the Trad-MCNIA system scored about the same value as human observation. In the medium and high frequency slides, MCN frequencies scored by the system were lower than those scored by human observers. This discrepancy was corrected by increasing the power of the objective of the microscope in the system. The MCN frequencies scored by the system attained 90% congruity with those scored by human observers after the correction. The scoring speed of the system was about 3.5 times as fast as that by human observers, and the data could be statistically analyzed immediately after the data scores were recorded. Further improvements can be made by upgrading the video camera and the computer speed.

Azides

A procedure for data analysis of the rodent micronucleus test involving a historical control.

No standard procedure of data analysis for rodent micronucleus tests involving historical controls has been established. In the present paper, under the presumption that the distribution of the historical control is stable and reliable, a procedure with three statistical steps is proposed to analyze the frequency of micronucleated polychromatic erythrocytes (MNPCEs). In the first step, the frequencies of MNPCEs in negative and positive control groups of a current experiment of the micronucleus test are compared with the distribution of historical negative and positive controls to examine the technical validity of the current experiment. In the second step, the frequency of MNPCEs in each treatment group is compared with the distribution of the historical negative control. In the third step, the dose-response relation is tested with the Cochran-Armitage trend test. A Monte Carlo stimulation study shows that the power of this procedure is acceptable and also this procedure is robust. An application of this procedure on real data reveals that it is effective in detecting clastogenic chemicals when the probability of a type I error is nearly .01.

Animals

Secondary data analysis: research method for the clinical nurse specialist.

This article presents a description of secondary data analysis and suggests that this type of research methodology may be helpful in facilitating research by the clinical nurse specialist (CNS). The article discusses the advantages and disadvantages of the use of this method specifically in relation to the CNS and offers suggestions for sources of data.

Data Collection

A simplified method of echocardiographic data analysis.

Rapid accurate analysis of echocardiographic data is accomplished using a sonic digitizer and programmable calculator. This method allows the echocardiographer to select technically optimal areas of the recording for analysis. The resolution of the measuring device is 0.1 mm. A hardcopy printout of both measurement and calculation is provided. Instead of expensive on-line computer, an inexpensive programmable calculator is used.

Computers

A consultation system constructor for medical data analysis.

MAD is a system that helps an expert data analyst in a specific application domain (like epidemiology or image analysis) to build reasoning models aimed at fulfilling specific tasks. These models may be subsequently used to guide doctors in the analysis of a set of data referring to a specific ground domain. Expert knowledge is represented at various levels: a general description of an application domain and various models that formalize the reasoning followed to perform specific tasks within a defined application domain. Reasoning models are represented as rules of propositional calculus, and a meta-knowledge permits to support knowledge acquisition. During the consultation, different external programs may be run when needed, without the doctor having to learn how to use them. MAD is written in Golden Common LISP and may be linked to any external software for data analysis, provided it runs under MS-DOS and does not require more than 192 Kb. Examples of application of the system to epidemiology and image analysis are given.

Computer Simulation

Constrained and restrained refinement in EXAFS data analysis with curved wave theory.

This paper describes methods of constrained and restrained refinement of EXAFS data which provide a means of substantially reducing the number of independent parameters compared to conventional least-squares methods commonly used. Constrained refinement allows a major reduction in the number of free parameters for a refinement of a structural model. In restrained refinement, additional structural information from well-characterized small molecules is used to provide additional observations in the data analysis. Even though these methods are of general application to the majority of complex systems, they are particularly valuable for biological molecules. The methods are of major advantage for ligands where significant multiple scattering is present, e.g., histidine, tyrosine, CO, CN, etc. The bases of these methods are described, and applications to some complex chemical and biological systems are given.

Fetal Hemoglobin

Analog processing of vestibular nystagmus for on-line cross- correlation data analysis.

An analog processing circuit is described which allow accurate measurement of the phase relationships between input angular acceleration and resulting eye velocity. Vestibular nystagmic data are processed via analog technics to yield slowphase eye velocity. The turntable velocity input is cross-correlated with the eye velocity output, using a Nicolet MED-80 minicomputer system. The resulting correlograms are further processed to obtain precise phase information. Test data analysis shows a system resolution within 1 degree. Data from human and animal subjects are portrayed.

Acceleration

Level of measurement: key to appropriate data analysis.

While PACU nurses are increasingly conducting research studies to validate nursing practice, it is important to consider logical rules for data analysis. Level of measurement is an important consideration when selecting statistical tests to analyze the data. Statistical tests need not remain a mystery since level of measurement is the deciding factor for selecting which tests are appropriate for answering the research questions or testing the hypotheses.

Clinical Nursing Research

Classification and discrimination for data analysis in pharmacology.

Classification and discrimination are described as methods of inference and decision-making in pharmacological data analysis. Principal components and multiple discriminant analysis are applied to animal and human spectra of the neuroleptics. A preliminary step is required to separate differences in potency from the spectral information.

Animals

Multivariate data analysis of sea waters and mussels in relation to pollution sources of trace elements.

The total concentration of Cu, Zn and Pb in surface sea waters from the Bay of Muggia (Gulf of Trieste, Northern Adriatic Sea) was determined by anodic stripping voltammetry. The association of these trace elements in relation to the known sources of pollution was discussed. The content of eight trace elements (Mn, Co, Ni, Cu, Zn, Cd, Hg, Pb) in the soft part of mussels (Mytilus galloprovincialis Lamarck) is also considered. The wild molluscs were sampled in the harbour of Trieste, in the proximity of an important city sewer. Principal component analysis was used to analyse the correlation matrix obtained from an 8 x 43 data matrix after a logarithmic transformation of the concentration variables. Eight variables were reduced to four principal components, which explained 80% of the total variance. The orthogonally rotated factor matrix shows that Co, Ni, Cd, and Pb are associated with the first principal component, Cu and Zn to the second, Hg to the third and Mn to the fourth principal component. The results of this multivariate data analysis are compared with those already obtained from two sampling sites in the Bay of Muggia and the origin of some trace metals in the soft part of mussels from the Gulf of Trieste is discussed.

Analysis of Variance

Diabetic autonomic neuropathy--Part I. Autonomic nervous system data analysis by a computerized central unit in a multicenter trial.

To determine the feasibility of utilizing a central, computerized unit to analyze autonomic nervous system function tests for a 10-year, multicenter, clinical trial, the Autonomic Nervous System Reading Center was established. The Reading Center selected and standardized testing methods, designed the testing protocol, developed testing equipment, computerized data analysis, and instituted measures to monitor data quality. Three cardiovascular testing methods, RR-variation, Valsalva maneuver, and postural testing, were selected because each is a simple, non-invasive, quantitative, sensitive, and reproducible test. Furthermore, a hierarchy of sensitivity has been established with these cardiovascular autonomic nervous system measurements: RR-variation, Valsalva maneuver, and finally postural testing. Confounding variables were minimized by prescribing eligibility criteria. Testing equipment, designed to record time between RR intervals in a form easily read into a computer, has been in 21 clinics for three years and a total of 54 technicians have been trained. Over 85 percent of the autonomic nervous system tests performed have been usable at initial testing. A central reading center is an efficient and necessary means of collecting and analyzing data for a multicenter clinical trial.

Autonomic Nervous System Diseases

The effects of overhead transparency design on retention, recall, and application of data analysis content.

This experimental study tested the effects of overhead transparency design in conjunction with live lecture on retention, recall, and application of data analysis content over three occasions using a Solomon Four-Group, pretest-posttest design. Pretested subjects showed significant (p less than .001) gains in test scores from pre to posttest. No significant differences were found in pretest scores between control and experimental treatment groups or among the posttest scores of either the experimental or control groups.

Audiovisual Aids

Multivariate data analysis in empirical research. A look on the bright side.

The interpretive benefits of employing multivariate analysis methods on experimental data with more than one dependent variable are described heuristically and illustrated on a set of data from a simply designed experiment in physiological psychology. Multivariate analysis of variance (MANOVA) is performed on the 9 dependent variables contained in the sample data and on the four composites derived from a principal components analysis (PCA) of the variability of the nine. A linear discriminant analysis (LDA) is conducted following both MANOVA results, and 5 methods of determining the "important" dependent variables in the experimental-control group difference are presented and discussed in terms of the data at hand.

Analysis of Variance

HLA-D typing with lymphoblastoid cell lines. VII. A computer program for data analysis.

When lymphoblastoid cell lines (LCL) are substituted for peripheral blood lymphocytes from human typing cell donors in HLA-D typing experiments, a data analysis program must be designed to distinguish the effect of allo-reactivity from those peculiar to LCL, mainly the "autologous-stimulation" effect. The computer program described in this report was created specifically for such an analysis. The rationale for the design of this program is presented in the preceding report (see this issue).

Cell Line

[Planning and data analysis in prospective controlled clinical trials (author's transl)].

Planning of prospective controlled clinical trials in surgery requires the use of test and control groups, sufficiently frequent repetition of experiments, random allocation of patients to the groups (example), and balancing. The descriptive data analysis should be performed in a stepwise manner (list of new data, rank list, range, median, quartiles, histogram, mean value standard deviation). The advantages of the median-quartile-system and the prerequisites for application of various significance tests are pointed out. In the conduct of controlled clinical trials, the consultative role of experimental surgeons is proposed.

Clinical Trials as Topic

Histopathological classification of dementias by multivariate data analysis.

Autopsied brains from 55 demented patients, clinically classified according to DSM-III criteria into AD/SDAT and MID and 19 nondemented individuals were available for this study. 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 AD-MID patients were 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.

Aged

Clinical assessment of the knowledge base of an expert system for data analysis in laboratory medicine.

Despite the apparent demand for a consultation system, only a few expert systems have been developed for laboratory medicine. Some studies on the diagnostic precision of such systems have been reported, but the efficiency of their knowledge bases has not yet been investigated. An expert system, named BLOOD, for data analysis in a hematology laboratory, which is written in C-Prolog and runs on VAX-station, has already been reported to have excellent diagnostic reliability and ability to cope with the fuzziness involved in clinical diagnostic procedures. A quantitative examination of the knowledge base of BLOOD using real laboratory data from 58 patients diagnosed as having iron deficiency anemia clearly revealed the verbosity of the knowledge base, and proved that it was effective for obtaining a group of essential diagnostic rules.

Anemia, Hypochromic