OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis.

Flow cytometry is used increasingly in clinical research for cancer, immunology and vaccines. Technological advances in cytometry instrumentation are increasing the size and dimensionality of data sets, posing a challenge for traditional data management and analysis. Automated analysis methods, despite a general consensus of their importance to the future of the field, have been slow to gain widespread adoption. Here we present OpenCyto, a new BioConductor infrastructure and data analysis framework designed to lower the barrier of entry to automated flow data analysis algorithms by addressing key areas that we believe have held back wider adoption of automated approaches. OpenCyto supports end-to-end data analysis that is robust and reproducible while generating results that are easy to interpret. We have improved the existing, widely used core BioConductor flow cytometry infrastructure by allowing analysis to scale in a memory efficient manner to the large flow data sets that arise in clinical trials, and integrating domain-specific knowledge as part of the pipeline through the hierarchical relationships among cell populations. Pipelines are defined through a text-based csv file, limiting the need to write data-specific code, and are data agnostic to simplify repetitive analysis for core facilities. We demonstrate how to analyze two large cytometry data sets: an intracellular cytokine staining (ICS) data set from a published HIV vaccine trial focused on detecting rare, antigen-specific T-cell populations, where we identify a new subset of CD8 T-cells with a vaccine-regimen specific response that could not be identified through manual analysis, and a CyTOF T-cell phenotyping data set where a large staining panel and many cell populations are a challenge for traditional analysis. The substantial improvements to the core BioConductor flow cytometry packages give OpenCyto the potential for wide adoption. It can rapidly leverage new developments in computational cytometry and facilitate reproducible analysis in a unified environment.

Standardizing Flow Cytometry Immunophenotyping Analysis from the Human ImmunoPhenotyping Consortium.

Standardization of immunophenotyping requires careful attention to reagents, sample handling, instrument setup, and data analysis, and is essential for successful cross-study and cross-center comparison of data. Experts developed five standardized, eight-color panels for identification of major immune cell subsets in peripheral blood. These were produced as pre-configured, lyophilized, reagents in 96-well plates. We present the results of a coordinated analysis of samples across nine laboratories using these panels with standardized operating procedures (SOPs). Manual gating was performed by each site and by a central site. Automated gating algorithms were developed and tested by the FlowCAP consortium. Centralized manual gating can reduce cross-center variability, and we sought to determine whether automated methods could streamline and standardize the analysis. Within-site variability was low in all experiments, but cross-site variability was lower when central analysis was performed in comparison with site-specific analysis. It was also lower for clearly defined cell subsets than those based on dim markers and for rare populations. Automated gating was able to match the performance of central manual analysis for all tested panels, exhibiting little to no bias and comparable variability. Standardized staining, data collection, and automated gating can increase power, reduce variability, and streamline analysis for immunophenotyping.

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data.

INTRODUCTION: The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful molecular signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities for more sophisticated approaches to integrating purely statistical and expert knowledge-based approaches. AREAS COVERED: In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered in deriving valid and useful signatures of disease. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. EXPERT OPINION: Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to identify predictive signatures of disease are key to future success in the biomarker field. We will describe our recommendations for possible approaches to this problem including metrics for the evaluation of biomarkers.

Allergic and nonallergic reactions to nitroglycerin.

Allergic and nonallergic reactions to nitroglycerin occur. The aims of this study were to review the different manifestations of nitroglycerin allergy, to explain how to evaluate for it, and to discuss its treatment. We reviewed relevant literature in peer-reviewed journals, computerized databases, and references identified from relevant bibliographics. Nitroglycerin's most common side effects are headache, facial flushing, head throbbing, fainting, hypotension, tachycardia, and syncope. The majority of reported skin reactions to topical and transdermal nitroglycerin products are irritant contact dermatitis, allergic contact dermatitis, and urticaria. Five cases of presumed allergic reactions to oral, sublingual, intravenous, or perianal nitroglycerin products have been described. Patch testing may be helpful in subjects with skin reactions to topical or transdermal nitroglycerin. In subjects with positive patch tests to nitroglycerin (allergic contact dermatitis), transdermal nitroglycerin patches and other topical nitroglycerin products should be avoided. Most patients with contact dermatitis to nitroglycerin have tolerated oral nitroglycerin, sublingual nitroglycerin, or oral isosorbide challenges.

Detection of prostate carcinoma with contrast-enhanced sonography using intermittent harmonic imaging.

BACKGROUND: The purpose of this study was to assess prostate carcinoma detection and discrimination of benign from malignant prostate tissue with contrast-enhanced ultrasonography. METHODS: In all, 301 subjects referred for prostate biopsy were evaluated with contrast-enhanced sonography using continuous harmonic imaging (CHI) and intermittent harmonic imaging (IHI) with interscan delay times of 0.2, 0.5, 1.0, 2.0 seconds, as well as continuous color and power Doppler. Targeted biopsy cores were obtained from sites of greatest enhancement, followed by spatially distributed cores in a modified sextant distribution. RESULTS: Carcinoma was detected in 363 biopsy cores from 104 of 301 subjects (35%). Carcinoma was found in 15.5% (175 of 1133) of targeted cores and 10.4% (188 of 1806) of sextant cores (P < 0.01). Among subjects with carcinoma, targeted cores were twice as likely to be positive (odds ratio [OR] = 2.0, P < 0.001). Clustered receiver operating characteristic (ROC) analysis of imaging findings at sextant biopsy sites yielded the following Az values: precontrast gray scale: 0.58; precontrast color Doppler: 0.53; precontrast power Doppler: 0.58; CHI: 0.62; IHI (0.2 sec): 0.64; IHI (0.5 sec): 0.63; IHI (1.0 sec): 0.65; IHI (2.0 sec): 0.61; contrast-enhanced color Doppler: 0.60; contrast-enhanced power Doppler: 0.62. A statistically significant benefit was found for IHI over baseline imaging (P < 0.05). CONCLUSIONS: The carcinoma detection rate of contrast-enhanced targeted cores is significantly higher when compared with sextant cores. Contrast-enhanced transrectal sonography with IHI provides a statistically significant improvement in discrimination between benign and malignant biopsy sites. However, given the relatively low ROC areas, this technique may not be sufficient to predict which patients have benign versus malignant disease.