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Introduction: Integrating social and environmental determinants of health (SEDoH) into enterprise-wide clinical workflows and decision-making is one of the most important and challenging aspects of improving health equity. We engaged domain experts to develop a SEDoH informatics maturity model (SIMM) to help guide organizations to address technical, operational, and policy gaps., Methods: We established a core expert group consisting of developers, informaticists, and subject matter experts to identify different SIMM domains and define maturity levels. The candidate model (v0.9) was evaluated by 15 informaticists at a Center for Data to Health community meeting. After incorporating feedback, a second evaluation round for v1.0 collected feedback and self-assessments from 35 respondents from the National COVID Cohort Collaborative, the Center for Leading Innovation and Collaboration's Informatics Enterprise Committee, and a publicly available online self-assessment tool., Results: We developed a SIMM comprising seven maturity levels across five domains: data collection policies, data collection methods and technologies, technology platforms for analysis and visualization, analytics capacity, and operational and strategic impact. The evaluation demonstrated relatively high maturity in analytics and technological capacity, but more moderate maturity in operational and strategic impact among academic medical centers. Changes made to the tool in between rounds improved its ability to discriminate between intermediate maturity levels., Conclusion: The SIMM can help organizations identify current gaps and next steps in improving SEDoH informatics. Improving the collection and use of SEDoH data is one important component of addressing health inequities., Competing Interests: JE is a paid consultant for Sanofi. The other authors declare no competing interests., (© The Author(s) 2023.)

Objective: Patient-reported outcome measures (PROMs) are critical to drive patient-centered care and to understanding patients' perspectives on their health status, quality of life, and the overall effectiveness of the care they receive. PROMs are increasingly being used in clinical and research settings, but the mechanisms to aggregate data from different systems can be cumbersome., Materials and Methods: As part of an FDA Real-World Evidence demonstration project, we enriched routine care clinical data from our Cerner electronic health record (EHR) with PROMs collected using REDCap. We used SSIS, sFTP, and the REDCap Application Programming Interface to aggregate both data sources into the Cerner HealtheIntent Population Health Platform., Results: We successfully built dashboards, reports, and datasets containing both REDCap and EHR data collected prospectively., Discussion: This technically straightforward approach using commonly available clinical and research tools can be readily adopted and adapted by others to better integrate PROMs with clinical data sources., Competing Interests: None declared., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background and Objective: Social and Environmental Determinants of Health (SEDoH) are of increasing interest to researchers in personal and public health. Collecting SEDoH and associating them with patient medical record can be challenging, especially for environmental variables. We announce here the release of SEnDAE, the Social and Environmental Determinants Address Enhancement toolkit, and open-source resource for ingesting a range of environmental variables and measurements from a variety of sources and associated them with arbitrary addresses., Methods: SEnDAE includes optional components for geocoding addresses, in case an organization does not have independent capabilities in that area, and recipes for extending the OMOP CDM and the ontology of an i2b2 instance to display and compute over the SEnDAE variables within i2b2., Results: On a set of 5000 synthetic addresses, SEnDAE was able to geocode 83%. SEnDAE geocodes addresses to the same Census tract as ESRI 98.1% of the time., Conclusion: Development of SEnDAE is ongoing, but we hope that teams will find it useful to increase their usage of environmental variables and increase the field's general understanding of these important determinants of health., Competing Interests: Declaration of Competing Interest JE is a paid consultant for AI Health. AI Health played no role in the design, execution, analysis, or write up of this work. AI Health did not play a role in the decision to publish this manuscript and had no editorial input., (Copyright © 2023. Published by Elsevier B.V.)

Clinical data networks that leverage large volumes of data in electronic health records (EHRs) are significant resources for research on coronavirus disease 2019 (COVID-19). Data harmonization is a key challenge in seamless use of multisite EHRs for COVID-19 research. We developed a COVID-19 application ontology in the national Accrual to Clinical Trials (ACT) network that enables harmonization of data elements that are critical to COVID-19 research. The ontology contains over 50 000 concepts in the domains of diagnosis, procedures, medications, and laboratory tests. In particular, it has computational phenotypes to characterize the course of illness and outcomes, derived terms, and harmonized value sets for severe acute respiratory syndrome coronavirus 2 laboratory tests. The ontology was deployed and validated on the ACT COVID-19 network that consists of 9 academic health centers with data on 14.5M patients. This ontology, which is freely available to the entire research community on GitHub at https://github.com/shyamvis/ACT-COVID-Ontology, will be useful for harmonizing EHRs for COVID-19 research beyond the ACT network., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Transcriptional regulation during CD4 + T cell fate decisions enables their differentiation into distinct states, guiding immune responses toward antibody production via Tfh cells or inflammation by Teff cells. Tfh-Teff cell fate commitment is regulated by mutual antagonism between the transcription factors Bcl6 and Blimp-1. Here we examined how T cell receptor (TCR) signals establish and arbitrate Bcl6-Blimp-1 counter-antagonism. We found that the TCR-signal-induced transcription factor Irf4 is essential for the differentiation of Bcl6-expressing Tfh and Blimp-1-expressing Teff cells. Increased TCR signaling raised Irf4 amounts and promoted Teff cell fates at the expense of Tfh ones. Importantly, orthogonal induction of Irf4 expression redirected Tfh cell fate trajectories toward those of Teff. Mechanistically, we linked greater Irf4 abundance with its recruitment toward low-affinity binding sites within Teff cell cis-regulatory elements, including those of Prdm1. We propose that the Irf4 locus functions as the "reader" of TCR signal strength, and in turn, concentration-dependent activity of Irf4 "writes" T helper fate choice., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Sickle cell disease (SCD) complications are associated with increased morbidity and risk of mortality. We sought to identify a circulating transcriptomic profile predictive of these poor outcomes in SCD. Training and testing cohorts consisting of adult patients with SCD were recruited and prospectively followed. A pathway-based signature derived from grouping peripheral blood mononuclear cell transcriptomes distinguished 2 patient clusters with differences in survival in the training cohort. These findings were validated in a testing cohort in which the association between cluster 1 molecular profiling and mortality remained significant in a fully adjusted model. In a third cohort of West African children with SCD, cluster 1 differentiated SCD severity using a published scoring index. Finally, a risk score composed of assigning weights to cluster 1 profiling, along with established clinical risk factors using tricuspid regurgitation velocity, white blood cell count, history of acute chest syndrome, and hemoglobin levels, demonstrated a higher hazard ratio for mortality in both the training and testing cohorts compared with clinical risk factors or cluster 1 data alone. Circulating transcriptomic profiles are a powerful method to risk-stratify severity of disease and poor outcomes in both children and adults, respectively, with SCD and highlight potential associated molecular pathways., (© 2017 by The American Society of Hematology.)

Background: The study of human lacrimal gland biology and development is limited. Lacrimal gland tissue is damaged or poorly functional in a number of disease states including dry eye disease. Development of cell based therapies for lacrimal gland diseases requires a better understanding of the gene expression and signaling pathways in lacrimal gland. Differential gene expression analysis between lacrimal gland and other embryologically similar tissues may be helpful in furthering our understanding of lacrimal gland development., Methods: We performed global gene expression analysis of human lacrimal gland tissue using Affymetrix ® gene expression arrays. Primary data from our laboratory was compared with datasets available in the NLM GEO database for other surface ectodermal tissues including salivary gland, skin, conjunctiva and corneal epithelium., Results: The analysis revealed statistically significant difference in the gene expression of lacrimal gland tissue compared to other ectodermal tissues. The lacrimal gland specific, cell surface secretory protein encoding genes and critical signaling pathways which distinguish lacrimal gland from other ectodermal tissues are described., Conclusions: Differential gene expression in human lacrimal gland compared with other ectodermal tissue types revealed interesting patterns which may serve as the basis for future studies in directed differentiation among other areas., Competing Interests: The authors have declared that no competing interests exist.

Altered nitric oxide (•NO) metabolism underlies cancer pathology, but mechanisms explaining many •NO-associated phenotypes remain unclear. We have found that cellular exposure to •NO changes histone posttranslational modifications (PTM) by directly inhibiting the catalytic activity of JmjC-domain containing histone demethylases. Herein, we describe how •NO exposure links modulation of histone PTMs to gene expression changes that promote oncogenesis. Through high-resolution mass spectrometry, we generated an extensive map of •NO-mediated histone PTM changes at 15 critical lysine residues on the core histones H3 and H4. Concomitant microarray analysis demonstrated that exposure to physiologic •NO resulted in the differential expression of over 6,500 genes in breast cancer cells. Measurements of the association of H3K9me2 and H3K9ac across genomic loci revealed that differential distribution of these particular PTMs correlated with changes in the level of expression of numerous oncogenes, consistent with epigenetic code. Our results establish that •NO functions as an epigenetic regulator of gene expression mediated by changes in histone PTMs., (©2015 American Association for Cancer Research.)

B lymphopoiesis requires that immunoglobulin genes be accessible to RAG1-RAG2 recombinase. However, the RAG proteins bind widely to open chromatin, which suggests that additional mechanisms must restrict RAG-mediated DNA cleavage. Here we show that developmental downregulation of interleukin 7 (IL-7)-receptor signaling in small pre-B cells induced expression of the bromodomain-family member BRWD1, which was recruited to a specific epigenetic landscape at Igk dictated by pre-B cell receptor (pre-BCR)-dependent Erk activation. BRWD1 enhanced RAG recruitment, increased gene accessibility and positioned nucleosomes 5' to each Jκ recombination signal sequence. BRWD1 thus targets recombination to Igk and places recombination within the context of signaling cascades that control B cell development. Our findings represent a paradigm in which, at any particular antigen-receptor locus, specialized mechanisms enforce lineage- and stage-specific recombination.

Background: Patient adherence to medication regimens is critical in most chronic disease treatment plans. This study uses a patient-centered tablet app, "My Interventional Drug-Eluting Stent Educational App (MyIDEA)." This is an educational program designed to improve patient medication adherence., Objective: Our goal is to describe the design, methodology, limitations, and results of the MyIDEA tablet app. We created a mobile technology-based patient education app to improve dual antiplatelet therapy adherence in patients who underwent a percutaneous coronary intervention and received a drug-eluting stent., Methods: Patient advisers were involved in the development process of MyIDEA from the initial wireframe to the final launch of the product. The program was restructured and redesigned based on the patient advisers' suggestions as well as those from multidisciplinary team members. To accommodate those with low health literacy, we modified the language and employed attractive color schemes to improve ease of use. We assumed that the target patient population may have little to no experience with electronic tablets, and therefore, we designed the interface to be as intuitive as possible., Results: The MyIDEA app has been successfully deployed to a low-health-literate elderly patient population in the hospital setting. A total of 6 patients have interacted with MyIDEA for an average of 17.6 minutes/session., Conclusions: Including patient advisers in the early phases of a mobile patient education development process is critical. A number of changes in text order, language, and color schemes occurred to improve ease of use. The MyIDEA program has been successfully deployed to a low-health-literate elderly patient population. Leveraging patient advisers throughout the development process helps to ensure implementation success.

In the United States, International Classification of Disease Clinical Modification (ICD-9-CM, the ninth revision) diagnosis codes are commonly used to identify patient cohorts and to conduct financial analyses related to disease. In October 2015, the healthcare system of the United States will transition to ICD-10-CM (the tenth revision) diagnosis codes. One challenge posed to clinical researchers and other analysts is conducting diagnosis-related queries across datasets containing both coding schemes. Further, healthcare administrators will manage growth, trends, and strategic planning with these dually-coded datasets. The majority of the ICD-9-CM to ICD-10-CM translations are complex and nonreciprocal, creating convoluted representations and meanings. Similarly, mapping back from ICD-10-CM to ICD-9-CM is equally complex, yet different from mapping forward, as relationships are likewise nonreciprocal. Indeed, 10 of the 21 top clinical categories are complex as 78% of their diagnosis codes are labeled as "convoluted" by our analyses. Analysis and research related to external causes of morbidity, injury, and poisoning will face the greatest challenges due to 41 745 (90%) convolutions and a decrease in the number of codes. We created a web portal tool and translation tables to list all ICD-9-CM diagnosis codes related to the specific input of ICD-10-CM diagnosis codes and their level of complexity: "identity" (reciprocal), "class-to-subclass," "subclass-to-class," "convoluted," or "no mapping." These tools provide guidance on ambiguous and complex translations to reveal where reports or analyses may be challenging to impossible.Web portal: http://www.lussierlab.org/transition-to-ICD9CM/Tables annotated with levels of translation complexity: http://www.lussierlab.org/publications/ICD10to9., (© The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Chronic glial activation and neuroinflammation induced by the amyloid-β peptide (Aβ) contribute to Alzheimer's disease (AD) pathology. APOE4 is the greatest AD-genetic risk factor; increasing risk up to 12-fold compared to APOE3, with APOE4-specific neuroinflammation an important component of this risk. This editorial review discusses the role of APOE in inflammation and AD, via a literature review, presentation of novel data on Aβ-induced neuroinflammation, and discussion of future research directions. The complexity of chronic neuroinflammation, including multiple detrimental and beneficial effects occurring in a temporal and cell-specific manner, has resulted in conflicting functional data for virtually every inflammatory mediator. Defining a neuroinflammatory phenotype (NIP) is one way to address this issue, focusing on profiling the changes in inflammatory mediator expression during disease progression. Although many studies have shown that APOE4 induces a detrimental NIP in peripheral inflammation and Aβ-independent neuroinflammation, data for APOE-modulated Aβ-induced neuroinflammation are surprisingly limited. We present data supporting the hypothesis that impaired apoE4 function modulates Aβ-induced effects on inflammatory receptor signaling, including amplification of detrimental (toll-like receptor 4-p38α) and suppression of beneficial (IL-4R-nuclear receptor) pathways. To ultimately develop APOE genotype-specific therapeutics, it is critical that future studies define the dynamic NIP profile and pathways that underlie APOE-modulated chronic neuroinflammation. In this editorial review, we present data supporting the hypothesis that impaired apoE4 function modulates Aβ-induced effects on inflammatory receptor signaling, including amplification of detrimental (TLR4-p38α) and suppression of beneficial (IL-4R-nuclear receptor) pathways, resulting in an adverse NIP that causes neuronal dysfunction. NIP, Neuroinflammatory phenotype; P.I., pro-inflammatory; A.I., anti-inflammatory., (© 2015 The Authors. Journal of Neurochemistry published by John Wiley & Sons Ltd on behalf of The International Society for Neurochemistry.)

Robust methods for identifying patterns of expression in genome-wide data are important for generating hypotheses regarding gene function. To this end, several analytic methods have been developed for detecting periodic patterns. We improve one such method, JTK_CYCLE, by explicitly calculating the null distribution such that it accounts for multiple hypothesis testing and by including non-sinusoidal reference waveforms. We term this method empirical JTK_CYCLE with asymmetry search, and we compare its performance to JTK_CYCLE with Bonferroni and Benjamini-Hochberg multiple hypothesis testing correction, as well as to five other methods: cyclohedron test, address reduction, stable persistence, ANOVA, and F24. We find that ANOVA, F24, and JTK_CYCLE consistently outperform the other three methods when data are limited and noisy; empirical JTK_CYCLE with asymmetry search gives the greatest sensitivity while controlling for the false discovery rate. Our analysis also provides insight into experimental design and we find that, for a fixed number of samples, better sensitivity and specificity are achieved with higher numbers of replicates than with higher sampling density. Application of the methods to detecting circadian rhythms in a metadataset of microarrays that quantify time-dependent gene expression in whole heads of Drosophila melanogaster reveals annotations that are enriched among genes with highly asymmetric waveforms. These include a wide range of oxidation reduction and metabolic genes, as well as genes with transcripts that have multiple splice forms.

The objective of this study is to determine the degree of similarities between the clinical terms used by physicians and nurses in their documentation.

Macrolides are clinically important antibiotics thought to inhibit bacterial growth by impeding the passage of newly synthesized polypeptides through the nascent peptide exit tunnel of the bacterial ribosome. Recent data challenged this view by showing that macrolide antibiotics can differentially affect synthesis of individual proteins. To understand the general mechanism of macrolide action, we used genome-wide ribosome profiling and analyzed the redistribution of ribosomes translating highly expressed genes in bacterial cells treated with high concentrations of macrolide antibiotics. The metagene analysis indicated that inhibition of early rounds of translation, which would be characteristic of the conventional view of macrolide action, occurs only at a limited number of genes. Translation of most genes proceeds past the 5'-proximal codons and can be arrested at more distal codons when the ribosome encounters specific short sequence motifs. The problematic sequence motifs are confined to the nascent peptide residues in the peptidyl transferase center but not to the peptide segment that contacts the antibiotic molecule in the exit tunnel. Therefore, it appears that the general mode of macrolide action involves selective inhibition of peptide bond formation between specific combinations of donor and acceptor substrates. Additional factors operating in the living cell but not functioning during in vitro protein synthesis may modulate site-specific action of macrolide antibiotics.

Background: The emergence of precision medicine allowed the incorporation of individual molecular data into patient care. Indeed, DNA sequencing predicts somatic mutations in individual patients. However, these genetic features overlook dynamic epigenetic and phenotypic response to therapy. Meanwhile, accurate personal transcriptome interpretation remains an unmet challenge. Further, N-of-1 (single-subject) efficacy trials are increasingly pursued, but are underpowered for molecular marker discovery., Method: 'N-of-1-pathways' is a global framework relying on three principles: (i) the statistical universe is a single patient; (ii) significance is derived from geneset/biomodules powered by paired samples from the same patient; and (iii) similarity between genesets/biomodules assesses commonality and differences, within-study and cross-studies. Thus, patient gene-level profiles are transformed into deregulated pathways. From RNA-Seq of 55 lung adenocarcinoma patients, N-of-1-pathways predicts the deregulated pathways of each patient., Results: Cross-patient N-of-1-pathways obtains comparable results with conventional genesets enrichment analysis (GSEA) and differentially expressed gene (DEG) enrichment, validated in three external evaluations. Moreover, heatmap and star plots highlight both individual and shared mechanisms ranging from molecular to organ-systems levels (eg, DNA repair, signaling, immune response). Patients were ranked based on the similarity of their deregulated mechanisms to those of an independent gold standard, generating unsupervised clusters of diametric extreme survival phenotypes (p=0.03)., Conclusions: The N-of-1-pathways framework provides a robust statistical and relevant biological interpretation of individual disease-free survival that is often overlooked in conventional cross-patient studies. It enables mechanism-level classifiers with smaller cohorts as well as N-of-1 studies., Software: http://lussierlab.org/publications/N-of-1-pathways., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

The Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN) represents an unprecedented collaboration across diverse healthcare institutions including private, county, and state hospitals and health systems, a consortium of Federally Qualified Health Centers, and two Department of Veterans Affairs hospitals. CAPriCORN builds on the strengths of our institutions to develop a cross-cutting infrastructure for sustainable and patient-centered comparative effectiveness research in Chicago. Unique aspects include collaboration with the University HealthSystem Consortium to aggregate data across sites, a centralized communication center to integrate patient recruitment with the data infrastructure, and a centralized institutional review board to ensure a strong and efficient human subject protection program. With coordination by the Chicago Community Trust and the Illinois Medical District Commission, CAPriCORN will model how healthcare institutions can overcome barriers of data integration, marketplace competition, and care fragmentation to develop, test, and implement strategies to improve care for diverse populations and reduce health disparities., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Unlabelled: Collecting data from large studies on high-throughput platforms, such as microarray or next-generation sequencing, typically requires processing samples in batches. There are often systematic but unpredictable biases from batch-to-batch, so proper randomization of biologically relevant traits across batches is crucial for distinguishing true biological differences from experimental artifacts. When a large number of traits are biologically relevant, as is common for clinical studies of patients with varying sex, age, genotype and medical background, proper randomization can be extremely difficult to prepare by hand, especially because traits may affect biological inferences, such as differential expression, in a combinatorial manner. Here we present ARTS (automated randomization of multiple traits for study design), which aids researchers in study design by automatically optimizing batch assignment for any number of samples, any number of traits and any batch size., Availability and Implementation: ARTS is implemented in Perl and is available at github.com/mmaiensc/ARTS. ARTS is also available in the Galaxy Tool Shed, and can be used at the Galaxy installation hosted by the UIC Center for Research Informatics (CRI) at galaxy.cri.uic.edu., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Gata5 is a transcription factor expressed in the lung, but its physiological role is unknown. To test whether and how Gata5 regulates airway constrictor responsiveness, we studied Gata5(-/-), Gata5(+/-), and wild-type mice on the C57BL/6J background. Cholinergic airway constrictor responsiveness was assessed invasively in mice without and with induction of allergic airway inflammation through ovalbumin sensitization and aerosol exposure. Gata5-deficient mice displayed native airway constrictor hyperresponsiveness (AHR) in the absence of allergen-induced inflammation. Gata5-deficient mice retained their relatively greater constrictor responsiveness even in ovalbumin-induced experimental asthma. Gata5 deficiency did not alter the distribution of cell types in bronchoalveolar lavage fluid, but bronchial epithelial mucus metaplasia was more prominent in Gata5(-/-) mice after allergen challenge. Gene expression profiles revealed that apolipoprotein E (apoE) was the fifth most down-regulated transcript in Gata5-deficient lungs, and quantitative RT-PCR and immunostaining confirmed reduced apoE expression in Gata5(-/-) mice. Quantitative RT-PCR also revealed increased IL-13 mRNA in the lungs of Gata5-deficient mice. These findings for the first time show that Gata5 regulates apoE and IL-13 expression in vivo and that its deletion causes AHR. Gata5-deficient mice exhibit an airway phenotype that closely resembles that previously reported for apoE(-/-) mice: both exhibit cholinergic AHR in native and experimental asthma states, and there is excessive goblet cell metaplasia after allergen sensitization and challenge. The Gata5-deficient phenotype also shares features that were previously reported for IL-13-treated mice. Together, these results indicate that Gata5 deficiency induces AHR, at least in part, by blunting apoE and increasing IL-13 expression.

Objective: Applying the science of networks to quantify the discriminatory impact of the ICD-9-CM to ICD-10-CM transition between clinical specialties., Materials and Methods: Datasets were the Center for Medicaid and Medicare Services ICD-9-CM to ICD-10-CM mapping files, general equivalence mappings, and statewide Medicaid emergency department billing. Diagnoses were represented as nodes and their mappings as directional relationships. The complex network was synthesized as an aggregate of simpler motifs and tabulation per clinical specialty., Results: We identified five mapping motif categories: identity, class-to-subclass, subclass-to-class, convoluted, and no mapping. Convoluted mappings indicate that multiple ICD-9-CM and ICD-10-CM codes share complex, entangled, and non-reciprocal mappings. The proportions of convoluted diagnoses mappings (36% overall) range from 5% (hematology) to 60% (obstetrics and injuries). In a case study of 24 008 patient visits in 217 emergency departments, 27% of the costs are associated with convoluted diagnoses, with 'abdominal pain' and 'gastroenteritis' accounting for approximately 3.5%., Discussion: Previous qualitative studies report that administrators and clinicians are likely to be challenged in understanding and managing their practice because of the ICD-10-CM transition. We substantiate the complexity of this transition with a thorough quantitative summary per clinical specialty, a case study, and the tools to apply this methodology easily to any clinical practice in the form of a web portal and analytic tables., Conclusions: Post-transition, successful management of frequent diseases with convoluted mapping network patterns is critical. The http://lussierlab.org/transition-to-ICD10CM web portal provides insight in linking onerous diseases to the ICD-10 transition.

In this manuscript, we present our experiences using the Apache Hadoop framework for high data volume and computationally intensive applications, and discuss some best practice guidelines in a clinical informatics setting. There are three main aspects in our approach: (a) process and integrate diverse, heterogeneous data sources using standard Hadoop programming tools and customized MapReduce programs; (b) after fine-grained aggregate results are obtained, perform data analysis using the Mahout data mining library; (c) leverage the column oriented features in HBase for patient centric modeling and complex temporal reasoning. This framework provides a scalable solution to meet the rapidly increasing, imperative "Big Data" needs of clinical and translational research. The intrinsic advantage of fault tolerance, high availability and scalability of Hadoop platform makes these applications readily deployable at the enterprise level cluster environment.

Latest genotyping solutions allow for rapid testing of more than two million markers in one experiment. Fully automated instruments such as Affymetrix GeneTitan enable processing of large numbers of samples in a truly high-throughput manner. In concert with solutions like Axiom, fully customizable array plates can now utilize automated workflows that can leverage multi-channel instrumentation like the GeneTitan. With the growing size of raw data output, the serial computational architecture of the software, typically distributed by the vendors on turnkey desktop solutions for quality control and genotype calling, becomes legacy rather than an advantage. Advanced software techniques provide power, flexibility, and can be deployed in an HPC environment, but become technically inconvenient for biologists to use. Here we present a pipeline that uses Galaxy as a mechanism to lower the barrier for complex analysis, and increase efficiency by leveraging high-throughput computing.

Objective: An area of need in cancer informatics is the ability to store images in a comprehensive database as part of translational cancer research. To meet this need, we have implemented a novel tandem database infrastructure that facilitates image storage and utilisation., Background: We had previously implemented the Thoracic Oncology Program Database Project (TOPDP) database for our translational cancer research needs. While useful for many research endeavours, it is unable to store images, hence our need to implement an imaging database which could communicate easily with the TOPDP database., Methods: The Thoracic Oncology Research Program (TORP) imaging database was designed using the Research Electronic Data Capture (REDCap) platform, which was developed by Vanderbilt University. To demonstrate proof of principle and evaluate utility, we performed a retrospective investigation into tumour response for malignant pleural mesothelioma (MPM) patients treated at the University of Chicago Medical Center with either of two analogous chemotherapy regimens and consented to at least one of two UCMC IRB protocols, 9571 and 13473A., Results: A cohort of 22 MPM patients was identified using clinical data in the TOPDP database. After measurements were acquired, two representative CT images and 0-35 histological images per patient were successfully stored in the TORP database, along with clinical and demographic data., Discussion: We implemented the TORP imaging database to be used in conjunction with our comprehensive TOPDP database. While it requires an additional effort to use two databases, our database infrastructure facilitates more comprehensive translational research., Conclusions: The investigation described herein demonstrates the successful implementation of this novel tandem imaging database infrastructure, as well as the potential utility of investigations enabled by it. The data model presented here can be utilised as the basis for further development of other larger, more streamlined databases in the future.