PASSIM – an open source software system for managing information in biomedical studies

BACKGROUND: One of the crucial aspects of day-to-day laboratory information management is collection, storage and retrieval of information about research subjects and biomedical samples. An efficient link between sample data and experiment results is absolutely imperative for a successful outcome of a biomedical study. Currently available software solutions are largely limited to large-scale, expensive commercial Laboratory Information Management Systems (LIMS). Acquiring such LIMS indeed can bring laboratory information management to a higher level, but often implies sufficient investment of time, effort and funds, which are not always available. There is a clear need for lightweight open source systems for patient and sample information management. RESULTS: We present a web-based tool for submission, management and retrieval of sample and research subject data. The system secures confidentiality by separating anonymized sample information from individuals' records. It is simple and generic, and can be customised for various biomedical studies. Information can be both entered and accessed using the same web interface. User groups and their privileges can be defined. The system is open-source and is supplied with an on-line tutorial and necessary documentation. It has proven to be successful in a large international collaborative project. CONCLUSION: The presented system closes the gap between the need and the availability of lightweight software solutions for managing information in biomedical studies involving human research subjects

A System for Information Management in BioMedical Studies—SIMBioMS

Summary: SIMBioMS is a web-based open source software system for managing data and information in biomedical studies. It provides a solution for the collection, storage, management and retrieval of information about research subjects and biomedical samples, as well as experimental data obtained using a range of high-throughput technologies, including gene expression, genotyping, proteomics and metabonomics. The system can easily be customized and has proven to be successful in several large-scale multi-site collaborative projects. It is compatible with emerging functional genomics data standards and provides data import and export in accepted standard formats. Protocols for transferring data to durable archives at the European Bioinformatics Institute have been implemented

Open source bioimage informatics for cell biology

Significant technical advances in imaging, molecular biology and genomics have fueled a revolution in cell biology, in that the molecular and structural processes of the cell are now visualized and measured routinely. Driving much of this recent development has been the advent of computational tools for the acquisition, visualization, analysis and dissemination of these datasets. These tools collectively make up a new subfield of computational biology called bioimage informatics, which is facilitated by open source approaches. We discuss why open source tools for image informatics in cell biology are needed, some of the key general attributes of what make an open source imaging application successful, and point to opportunities for further operability that should greatly accelerate future cell biology discovery

SaDA: From Sampling to Data Analysis—An Extensible Open Source Infrastructure for Rapid, Robust and Automated Management and Analysis of Modern Ecological High-Throughput Microarray Data

One of the most crucial characteristics of day-to-day laboratory information management is the collection, storage and retrieval of information about research subjects and environmental or biomedical samples. An efficient link between sample data and experimental results is absolutely important for the successful outcome of a collaborative project. Currently available software solutions are largely limited to large scale, expensive commercial Laboratory Information Management Systems (LIMS). Acquiring such LIMS indeed can bring laboratory information management to a higher level, but most of the times this requires a sufficient investment of money, time and technical efforts. There is a clear need for a light weighted open source system which can easily be managed on local servers and handled by individual researchers. Here we present a software named SaDA for storing, retrieving and analyzing data originated from microorganism monitoring experiments. SaDA is fully integrated in the management of environmental samples, oligonucleotide sequences, microarray data and the subsequent downstream analysis procedures. It is simple and generic software, and can be extended and customized for various environmental and biomedical studies

SLIMS—a user-friendly sample operations and inventory management system for genotyping labs

Summary: We present the Sample-based Laboratory Information Management System (SLIMS), a powerful and user-friendly open source web application that provides all members of a laboratory with an interface to view, edit and create sample information. SLIMS aims to simplify common laboratory tasks with tools such as a user-friendly shopping cart for subjects, samples and containers that easily generates reports, shareable lists and plate designs for genotyping. Further key features include customizable data views, database change-logging and dynamically filled pre-formatted reports. Along with being feature-rich, SLIMS' power comes from being able to handle longitudinal data from multiple time-points and biological sources. This type of data is increasingly common from studies searching for susceptibility genes for common complex diseases that collect thousands of samples generating millions of genotypes and overwhelming amounts of data. LIMSs provide an efficient way to deal with this data while increasing accessibility and reducing laboratory errors; however, professional LIMS are often too costly to be practical. SLIMS gives labs a feasible alternative that is easily accessible, user-centrically designed and feature-rich. To facilitate system customization, and utilization for other groups, manuals have been written for users and developers

LabKey Server: An open source platform for scientific data integration, analysis and collaboration

<p>Abstract</p> <p>Background</p> <p>Broad-based collaborations are becoming increasingly common among disease researchers. For example, the Global HIV Enterprise has united cross-disciplinary consortia to speed progress towards HIV vaccines through coordinated research across the boundaries of institutions, continents and specialties. New, end-to-end software tools for data and specimen management are necessary to achieve the ambitious goals of such alliances. These tools must enable researchers to organize and integrate heterogeneous data early in the discovery process, standardize processes, gain new insights into pooled data and collaborate securely.</p> <p>Results</p> <p>To meet these needs, we enhanced the LabKey Server platform, formerly known as CPAS. This freely available, open source software is maintained by professional engineers who use commercially proven practices for software development and maintenance. Recent enhancements support: (i) Submitting specimens requests across collaborating organizations (ii) Graphically defining new experimental data types, metadata and wizards for data collection (iii) Transitioning experimental results from a multiplicity of spreadsheets to custom tables in a shared database (iv) Securely organizing, integrating, analyzing, visualizing and sharing diverse data types, from clinical records to specimens to complex assays (v) Interacting dynamically with external data sources (vi) Tracking study participants and cohorts over time (vii) Developing custom interfaces using client libraries (viii) Authoring custom visualizations in a built-in R scripting environment.</p> <p>Diverse research organizations have adopted and adapted LabKey Server, including consortia within the Global HIV Enterprise. Atlas is an installation of LabKey Server that has been tailored to serve these consortia. It is in production use and demonstrates the core capabilities of LabKey Server. Atlas now has over 2,800 active user accounts originating from approximately 36 countries and 350 organizations. It tracks roughly 27,000 assay runs, 860,000 specimen vials and 1,300,000 vial transfers.</p> <p>Conclusions</p> <p>Sharing data, analysis tools and infrastructure can speed the efforts of large research consortia by enhancing efficiency and enabling new insights. The Atlas installation of LabKey Server demonstrates the utility of the LabKey platform for collaborative research. Stable, supported builds of LabKey Server are freely available for download at <url>http://www.labkey.org</url>. Documentation and source code are available under the Apache License 2.0.</p

Handheld computers for self-administered sensitive data collection: A comparative study in Peru

<p>Abstract</p> <p>Background</p> <p>Low-cost handheld computers (PDA) potentially represent an efficient tool for collecting sensitive data in surveys. The goal of this study is to evaluate the quality of sexual behavior data collected with handheld computers in comparison with paper-based questionnaires.</p> <p>Methods</p> <p>A PDA-based program for data collection was developed using Open-Source tools. In two cross-sectional studies, we compared data concerning sexual behavior collected with paper forms to data collected with PDA-based forms in Ancon (Lima).</p> <p>Results</p> <p>The first study enrolled 200 participants (18–29 years). General agreement between data collected with paper format and handheld computers was 86%. Categorical variables agreement was between 70.5% and 98.5% (Kappa: 0.43–0.86) while numeric variables agreement was between 57.1% and 79.8% (Spearman: 0.76–0.95). Agreement and correlation were higher in those who had completed at least high school than those with less education. The second study enrolled 198 participants. Rates of responses to sensitive questions were similar between both kinds of questionnaires. However, the number of inconsistencies (p = 0.0001) and missing values (p = 0.001) were significantly higher in paper questionnaires.</p> <p>Conclusion</p> <p>This study showed the value of the use of handheld computers for collecting sensitive data, since a high level of agreement between paper and PDA responses was reached. In addition, a lower number of inconsistencies and missing values were found with the PDA-based system. This study has demonstrated that it is feasible to develop a low-cost application for handheld computers, and that PDAs are feasible alternatives for collecting field data in a developing country.</p