Case #1

Academic research project on a complex disease

The customer is an academic genetic research group studying a complex disease. For their research, they collect and maintain a patient cohort with high prevalence of the disease. Research nurses meet the patients once a year, collect comprehensive patient data using questionnaires and produce laboratory data. They also record patient family relations by drawing pedigrees. In addition to collecting new data, they give the patients reports on laboratory and other results produced by the research center. To reach as many patients as possible, data is collected in many centers around the country. High-throughput genotyping and sequencing efforts are outsourced to a genome center, but smaller re-sequencing projects are performed at the customer’s own laboratory.

All the project data is collected to a BC server hosted by the university IT department. For computing intensive data analyses, the server is connected to a university calculation cluster. As the group uses patient health and genomic data, high level data security measures for both the BC platform and applications, as well as server hardware are in place.

Patient questionnaires, pedigrees, and laboratory values are directly entered or uploaded to the server by the nurses. The system also provides an application for pedigree drawing. Genotype and processed sequence data from the genome center are uploaded to the BC|GENOME database by researchers. For locally produced sequence data, alignment and variation calling are performed by the BC|GENOME application.

For statistical genetic data analyses, the researcher can choose between many different academic packages supported by the system and their own scripts and tools. Some users prefer the easy-to-use web-interface, while others prefer the command line tools provided. In addition to producing input files for different packages, BC|GENOME splits analysis tasks to small segments, and runs them in parallel in the university calculation cluster.

Case #2

Sample repository and genotyping service

Collaborating parties have pooled together their different expertise in certain methodologies and created a working solution for collecting and analyzing specific disease samples in multiple different ways.

BC|SAMPLE and BC|CLIN modules are used in a genotyping laboratory to keep track of collaborators’ samples, and their clinical context. Samples are sent over, registered in BC|SAMPLE, and processed using the saved workflows in the module. PCR genotyping is routinely and repeatedly run on the samples for about 20+ mutations, and BC|SAMPLE retains information about each run and its results. These results are overlaid with the original registered sample information to create a view of genotyping progress. The results of the 20+ PCRs can be immediately seen for each sample, and the laboratory technicians are able to export the data for sample owners.

In addition, another collaborator, who uses BC|CLIN to manage the clinical data associated with the sample collection, is able to directly extract genotype PCR results from the genotyping laboratory’s BC|SAMPLE, to be saved with the clinical and genetic data. The collaborator’s link to the PCR results is restricted to only those samples in their project, and all data transfers are encrypted.

Case #3

Genotype knowledge base for pharmaceutical industry

As an example solution for the pharmaceutical industry, we have used our modules to build a disease specific solution. In this case the pharmaceutical company collects various formats of data from both in-house sources as well as from external collaborators and published material.

Data includes genotype data (SNP chip) produced at collaborating academic facilities, clinical data, and data on drug use and adverse side effects. The system is connected to an in-house computing cluster for imputing, statistical analysis for correlation between SNPs and drug efficacy, adverse effects and other clinical data.
The system is also used as an effective internal communication tool between researchers.

Case #4

Research biobank

The customer uses a 3rd party LIMS system in conjunction with the BC|CLIN phenotype data management application. In addition, the BC|GENOME application manages various other data types, including genealogy, genotype, sequence, copy number variation and different -‘omics’ data types.

The customer’s biobank collaboration policy encourages the collaborating third parties to turn in their research data to the biobank. Data can be any type of genomic data, laboratory values, patient questionnaires, etc. By using the form editor application, all existing data structures can be easily modified to be cohesive, facilitating the storing of all received data to the database.

The BC platform can scale up to population level data amounts, including whole genome data. The platform has inbuilt security features, including full log files and user and group level data access limitations. It can be connected to a local authentication system or used through strong authentication systems like RSA.

Case #5

Biobank combining electronic health record (EHR) and genomic data

This university hospital runs a biobank that is continuously used to recruit patients for clinical research studies. The recruited patients participate by giving a DNA sample and an informed consent to use all of their data in the hospital’s records for research. All patients are genotyped and then imputed using the BC|GENOME system.

For research, relevant data from EHRs (Electronic Health Record) is integrated with the platform for statistical genetic data analysis. In order to analyze massive data amounts, the BC|GENOME application is connected to the calculation cluster of the university. The customer uses primarily common academic analysis tools, but also some special tools that have been developed in-house. Both types of tools are integrated with the BC platform.

Case #6

Research consortium collaborative biobank

In this case the customer is a research consortium working with the same rare disease. They collaborate to recruit enough patients for a successful genome wide association (GWAS) project. They designed a standard patient questionnaire that all new patients should answer. For existing patients, the questionnaire is completed using existing information. In addition to the questionnaires, information about available DNA samples is shared.

Many of the sample and data collections are strictly controlled by data privacy rules and patient consents, which makes data sharing complicated. Partners in the consortium are allowed to analyze the data, but the data cannot be transferred outside the approved storage. This puts special requirements for the solutions for data protection and sharing.

BC Platforms has set up a hosted BC|GENOME platform to serve as the central database for the project. The platform is used to share the data and to perform all the data analyses. As all the commonly used data analysis tools are included, data analyses can be performed inside the system, without any need to export it. Using the unique BC|SAFEBOX, data can also be analyzed using a researcher’s own scripts and workflows without compromising the data security.

Want to know more? Let’s talk

Get in touch