ANSWER: Annotation Software for Electronic Reporting

PURPOSE To better use genetic testing, which is used by clinicians to explain the molecular mechanism of disease and to suggest clinical actionability and new treatment options, clinical next-generation sequencing (NGS) laboratories must send the results into reports in PDF and discrete data element format (HL7). Although most clinical diagnostic tests have set molecular markers tested and have a set range of values or a binary result (positive or negative), the NGS genetic test could examine hundreds or thousands of genes with no predefined list of variants. Although there are some commercial and open-source tools for clinically reporting genomics results for oncology testing, they often lack necessary features. METHODS Using several available software tools for data storage including MySQL and MongoDB, database querying with Python, and a web-based user application using JAVA and JAVA script, we have developed a tool to store and query complex genomics and demographics data, which can be manually curated and reported by the user. RESULTS We have developed a tool, Annotation SoftWare for Electronic Reporting (ANSWER), that can allow molecular pathologists to (1) filter variants to find those meeting quality control metrics in the genes that are clinically actionable by diagnosis; (2) visualize variants using data generated in the bioinformatics analysis; (3) create annotations that can be reused in future reports with association specific to the gene, variant, or diagnosis; (4) select variants and annotations that should be reported to match the details of the case; and (5) generate a report that includes demographics, reported variants, clinical actionability annotation, and references that can be exported into PDF or HL7 format, which can be electronically sent to an electronic health record. CONCLUSION ANSWER is a tool that can be installed locally and is designed to meet the clinical reporting needs of a clinical oncology NGS laboratory for reporting.

Participatory Design of a Clinical Trial Eligibility Criteria Simplification Method

Clinical trial eligibility criteria are important for selecting the right participants for clinical trials. However, they are often complex and not computable. This paper presents the participatory design of a human-computer collaboration method for criteria simplification that includes natural language processing followed by user-centered eligibility criteria simplification. A case study on the ARCADIA trial shows how criteria were simplified for structured database querying by clinical researchers and identifies rules for criteria simplification and concept normalization.

Mobile Maps and More - Extending Location-Based Services with Multi-Criteria Decision Analysis

Maps are often used as decision support tools in both, desktop geographic information systems (GIS) and mobile GIS environments. The decision support capabilities of current location-based services (LBS) are limited to navigation support and database querying with no analytic evaluation of the attractiveness of alternative destinations being offered. This chapter demonstrates how LBS can be extended with specific decision support functionality, namely multi-criteria decision analysis (MCDA). MCDA was recently transferred to the mobile GIS platform illustrating how LBS user preferences can be represented by the parameters in a MCDA method and will lead to personalized decision outcomes. An extension to a collaborative crisis management scenario is proposed, in which mobile decision-makers have MCDA tools at hand to help them make more informed choices. This chapter describes the scenario and derives a client/server architecture as well as the user interface and map design for a mobile decision support system for emergency response.

Containment of Simple Conjunctive Regular Path Queries

Testing containment of queries is a fundamental reasoning task in knowledge representation. We study here the containment problem for Conjunctive Regular Path Queries (CRPQs), a navigational query language extensively used in ontology and graph database querying. While it is known that containment of CRPQs is EXPSPACE-complete in general, we focus here on severely restricted fragments, which are known to be highly relevant in practice according to several recent studies. We obtain a detailed overview of the complexity of the containment problem, depending on the features used in the regular expressions of the queries, with completeness results for NP, Pi2p, PSPACE or EXPSPACE.

Lipid Related Genes Altered in NASH Connect Inflammation in Liver Pathogenesis Progression to HCC: A Canonical Pathway

Nonalcoholic steatohepatitis (NASH) is becoming a public health problem worldwide. While the number of research studies on NASH progression rises every year, sometime their findings are controversial. To identify the most important and commonly described findings related to NASH progression, we used an original bioinformatics, integrative, text-mining approach that combines PubMed database querying and available gene expression omnibus dataset. We have identified a signature of 25 genes that are commonly found to be dysregulated during steatosis progression to NASH and cancer. These genes are implicated in lipid metabolism, insulin resistance, inflammation, and cancer. They are functionally connected, forming the basis necessary for steatosis progression to NASH and further progression to hepatocellular carcinoma (HCC). We also show that five of the identified genes have genome alterations present in HCC patients. The patients with these genes associated to genome alteration are associated with a poor prognosis. In conclusion, using an integrative literature- and data-mining approach, we have identified and described a canonical pathway underlying progression of NASH. Other parameters (e.g. polymorphisms) can be added to this pathway that also contribute to the progression of the disease to cancer. This work improved our understanding of the molecular basis of NASH progression and will help to develop new therapeutic approaches.

VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium

Here, we report an update of the VDJdb database with a substantial increase in the number of T-cell receptor (TCR) sequences and their cognate antigens. The update further provides a new database infrastructure featuring two additional analysis modes that facilitate database querying and real-world data analysis. The increased yield of TCR specificity identification methods and the overall increase in the number of studies in the field has allowed us to expand the database more than 5-fold. Furthermore, several new analysis methods are included. For example, batch annotation of TCR repertoire sequencing samples allows for annotating large datasets on-line. Using recently developed bioinformatic methods for TCR motif mining, we have built a reduced set of high-quality TCR motifs that can be used for both training TCR specificity predictors and matching against TCRs of interest. These additions enhance the versatility of the VDJdb in the task of exploring T-cell antigen specificities. The database is available at https://vdjdb.cdr3.net.