Showing papers by "Brigham Young University published in 2015"

Loneliness and Social Isolation as Risk Factors for Mortality: A Meta-Analytic Review

Abstract: Actual and perceived social isolation are both associated with increased risk for early mortality. In this meta-analytic review, our objective is to establish the overall and relative magnitude of social isolation and loneliness and to examine possible moderators. We conducted a literature search of studies (January 1980 to February 2014) using MEDLINE, CINAHL, PsycINFO, Social Work Abstracts, and Google Scholar. The included studies provided quantitative data on mortality as affected by loneliness, social isolation, or living alone. Across studies in which several possible confounds were statistically controlled for, the weighted average effect sizes were as follows: social isolation odds ratio (OR) = 1.29, loneliness OR = 1.26, and living alone OR = 1.32, corresponding to an average of 29%, 26%, and 32% increased likelihood of mortality, respectively. We found no differences between measures of objective and subjective social isolation. Results remain consistent across gender, length of follow-up, and world region, but initial health status has an influence on the findings. Results also differ across participant age, with social deficits being more predictive of death in samples with an average age younger than 65 years. Overall, the influence of both objective and subjective social isolation on risk for mortality is comparable with well-established risk factors for mortality.

Improvements from a Flipped Classroom May Simply Be the Fruits of Active Learning.

Abstract: Researchers show that students perform equally well in flipped and nonflipped classrooms if active-learning activities are held constant, suggesting that active learning is the key moderator of suc...

Measuring student engagement in technology-mediated learning

Abstract: Using digital technology to deliver content, connect learners, and enable anytime, anywhere learning is increasing, but keeping students engaged in technology-mediated learning is challenging. Instructional practices that encourage greater engagement are essential if we are to effectively use digital instructional technologies. To determine the impact of innovative instructional practices on learning, we need useful measures of student engagement. These measures should be adaptable to the unique challenges to studying technology-mediated learning, such as when students learn at a distance or in a blended learning course. In this review, we examine existing approaches to measure engagement in technology-mediated learning. We identify strengths and limitations of existing measures and outline potential approaches to improve the measurement of student engagement. Our intent is to assist researchers, instructors, designers, and others in identifying effective methods to conceptualize and measure student engagement in technology-mediated learning. Consensus is needed for the definition and operationalization of student engagement.Most technology-mediated learning research uses self-report measures of engagement.Physiological and systems data offer an alternative method to measuring engagement.More research is needed to study the role of emotional engagement in learning.More research needed to determine value of physiological and systems data.

Behavioral Functionality of Mobile Apps in Health Interventions: A Systematic Review of the Literature

Abstract: Background: Several thousand mobile phone apps are available to download to mobile phones for health and fitness. Mobile phones may provide a unique means of administering health interventions to populations. Objective: The purpose of this systematic review was to systematically search and describe the literature on mobile apps used in health behavior interventions, describe the behavioral features and focus of health apps, and to evaluate the potential of apps to disseminate health behavior interventions. Methods: We conducted a review of the literature in September 2014 using key search terms in several relevant scientific journal databases. Only English articles pertaining to health interventions using mobile phone apps were included in the final sample. Results: The 24 studies identified for this review were primarily feasibility and pilot studies of mobile apps with small sample sizes. All studies were informed by behavioral theories or strategies, with self-monitoring as the most common construct. Acceptability of mobile phone apps was high among mobile phone users. Conclusions: The lack of large sample studies using mobile phone apps may signal a need for additional studies on the potential use of mobile apps to assist individuals in changing their health behaviors. Of these studies, there is early evidence that apps are well received by users. Based on available research, mobile apps may be considered a feasible and acceptable means of administering health interventions, but a greater number of studies and more rigorous research and evaluations are needed to determine efficacy and establish evidence for best practices. [JMIR Mhealth Uhealth 2015;3(1):e20]

Factors That Influence the Development of Compassion Fatigue, Burnout, and Compassion Satisfaction in Emergency Department Nurses

Abstract: Purpose The purpose of this study was twofold: (a) to determine the prevalence of compassion satisfaction, compassion fatigue, and burnout in emergency department nurses throughout the United States and (b) to examine which demographic and work-related components affect the development of compassion satisfaction, compassion fatigue, and burnout in this nursing specialty. Design and Methods This was a nonexperimental, descriptive, and predictive study using a self-administered survey. Survey packets including a demographic questionnaire and the Professional Quality of Life Scale version 5 (ProQOL 5) were mailed to 1,000 selected emergency nurses throughout the United States. The ProQOL 5 scale was used to measure the prevalence of compassion satisfaction, compassion fatigue, and burnout among emergency department nurses. Multiple regression using stepwise solution was employed to determine which variables of demographics and work-related characteristics predicted the prevalence of compassion satisfaction, compassion fatigue, and burnout. The α level was set at .05 for statistical significance. Findings The results revealed overall low to average levels of compassion fatigue and burnout and generally average to high levels of compassion satisfaction among this group of emergency department nurses. The low level of manager support was a significant predictor of higher levels of burnout and compassion fatigue among emergency department nurses, while a high level of manager support contributed to a higher level of compassion satisfaction. Conclusions The results may serve to help distinguish elements in emergency department nurses’ work and life that are related to compassion satisfaction and may identify factors associated with higher levels of compassion fatigue and burnout. Clinical Relevance Improving recognition and awareness of compassion satisfaction, compassion fatigue, and burnout among emergency department nurses may prevent emotional exhaustion and help identify interventions that will help nurses remain empathetic and compassionate professionals.

The beetle tree of life reveals that Coleoptera survived end‐Permian mass extinction to diversify during the Cretaceous terrestrial revolution

Abstract: © 2015 The Authors. Systematic Entomology published by John Wiley & Sons Ltd on behalf of Royal Entomological Society This is an open access article under the terms of the Creative Commons AttributionߚNonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Ambient PM2.5, O3, and NO2 Exposures and Associations with Mortality over 16 Years of Follow-Up in the Canadian Census Health and Environment Cohort (CanCHEC)

Abstract: BackgroundFew studies examining the associations between long-term exposure to ambient air pollution and mortality have considered multiple pollutants when assessing changes in exposure due to resi...

Implementing routine outcome monitoring in clinical practice: Benefits, challenges, and solutions

Abstract: This article reviews the benefits, obstacles, and challenges that can hinder (and have hindered) implementation of routine outcome monitoring in clinical practice. Recommendations for future routine outcome assessment efforts are also provided. Spanning three generations, as well as multiple developed tools and approaches, the four authors of this article have spent much of their careers working to address these issues and attempt to consolidate this learning and experience briefly here. Potential "elephants in the room" are brought into the discussion wherever relevant, rather than leaving them to obstruct silently the field's efforts. Some of these topics have been largely ignored, yet must be addressed if we are to fulfill our promise of integrating science and practice. This article is an attempt to identify these important issues and start an honest and open dialogue.

Relationships Between Fine Particulate Air Pollution, Cardiometabolic Disorders, and Cardiovascular Mortality

Abstract: Rationale: Growing evidence suggests that long-term exposure to fine particulate matter (PM 2.5 ) air pollution contributes to risk of cardiovascular disease (CVD) morbidity and mortality. There is uncertainty about who are most susceptible. Individuals with underlying cardiometabolic disorders, including hypertension, diabetes mellitus, and obesity, may be at greater risk. PM 2.5 pollution may also contribute to cardiometabolic disorders, augmenting CVD risk. Objective: This analysis evaluates relationships between long-term PM 2.5 exposure and cardiometabolic disease on risk of death from CVD and cardiometabolic conditions. Methods and Results: Data on 669 046 participants from the American Cancer Society Cancer Prevention Study II cohort were linked to modeled PM 2.5 concentrations at geocoded home addresses. Cox proportional hazards regression models were used to estimate adjusted hazards ratios for death from CVD and cardiometabolic diseases based on death-certificate information. Effect modification by pre-existing cardiometabolic risk factors on the PM 2.5 –CVD mortality association was examined. PM 2.5 exposure was associated with CVD mortality, with the hazards ratios (95% confidence interval) per 10 μg/m 3 increase in PM 2.5 equal to 1.12 (1.10–1.15). Deaths linked to hypertension and diabetes mellitus (mentioned on death certificate as either primary or contributing cause of death) were also associated with PM 2.5 . There was no consistent evidence of effect modification by cardiometabolic disease risk factors on the PM 2.5 –CVD mortality association. Conclusions: Pollution-induced CVD mortality risk is observed for those with and without existing cardiometabolic disorders. Long-term exposure may also contribute to the development or exacerbation of cardiometabolic disorders, increasing risk of CVD, and cardiometabolic disease mortality.

Randomization Inference in the Regression Discontinuity Design: An Application to Party Advantages in the U.S. Senate

Abstract: In the Regression Discontinuity (RD) design, units are assigned a treatment based on whether their value of an observed covariate is above or below a fixed cutoff. Under the assumption that the distribution of potential confounders changes continuously around the cutoff, the discontinuous jump in the probability of treatment assignment can be used to identify the treatment effect. Although a recent strand of the RD literature advocates interpreting this design as a local randomized experiment, the standard approach to estimation and inference is based solely on continuity assumptions that do not justify this interpretation. In this article, we provide precise conditions in a randomization inference context under which this interpretation is directly justified and develop exact finite-sample inference procedures based on them. Our randomization inference framework is motivated by the observation that only a few observations might be available close enough to the threshold where local randomization is plausible, and hence standard large-sample procedures may be suspect. Our proposed methodology is intended as a complement and a robustness check to standard RD inference approaches. We illustrate our framework with a study of two measures of party-level advantage in U.S. Senate elections, where the number of close races is small and our framework is well suited for the empirical analysis.

Perspective: Sloppiness and emergent theories in physics, biology, and beyond

Abstract: Large scale models of physical phenomena demand the development of new statistical and computational tools in order to be effective. Many such models are “sloppy,” i.e., exhibit behavior controlled by a relatively small number of parameter combinations. We review an information theoretic framework for analyzing sloppy models. This formalism is based on the Fisher information matrix, which is interpreted as a Riemannian metric on a parameterized space of models. Distance in this space is a measure of how distinguishable two models are based on their predictions. Sloppy model manifolds are bounded with a hierarchy of widths and extrinsic curvatures. The manifold boundary approximation can extract the simple, hidden theory from complicated sloppy models. We attribute the success of simple effective models in physics as likewise emerging from complicated processes exhibiting a low effective dimensionality. We discuss the ramifications and consequences of sloppy models for biochemistry and science more generally. We suggest that the reason our complex world is understandable is due to the same fundamental reason: simple theories of macroscopic behavior are hidden inside complicated microscopic processes.

The Interplay Between Sensory Processing Abnormalities, Intolerance of Uncertainty, Anxiety and Restricted and Repetitive Behaviours in Autism Spectrum Disorder

Abstract: Sensory processing abnormalities, anxiety and restricted and repetitive behaviours (RRBs) frequently co-occur in Autism Spectrum Disorders (ASD). Though the relationship between these phenomena is not well understood, emerging evidence indicates intolerance of uncertainty (IU) may play an important role. This study aimed to determine pathways between sensory abnormalities and RRBs, and the role anxiety and IU may have. We gathered caregiver report data for 53 children with ASD aged 8–16 years. We found sensory under responsiveness and sensory over responsiveness were significantly associated with repetitive motor and insistence on sameness behaviours, and the relationships significantly mediated by IU and anxiety. Our findings indicate different mechanisms may underpin repetitive motor and insistence on sameness RRBs, which can inform treatment interventions.

Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans

Abstract: Introduction Genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) have been crucial in advancing the understanding of Alzheimer's disease (AD) pathophysiology. Here, we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans. Methods Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing data have been obtained and disseminated. Results ADNI genetic data have been downloaded thousands of times, and >300 publications have resulted, including reports of large-scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies used ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first whole exome and whole genome sequencing data sets and reports in healthy controls, mild cognitive impairment, and AD. Discussion Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multiomics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological processes. Fortunately, a broad swath of the scientific community has accepted this grand challenge.

Leader narcissism and follower outcomes: The counterbalancing effect of leader humility.

Abstract: [Correction Notice: An Erratum for this article was reported in Vol 100(4) of Journal of Applied Psychology (see record 2015-29666-001). The last name of the second author was misspelled in the Online First version of the article. All versions of this article have been corrected.] In response to recent calls to theorize and examine how multiple leader characteristics may work together in their effects, the current research examines how leader narcissism and humility interact to predict perceived leader effectiveness and follower (i.e., direct-report) job engagement and performance. Although an examination of leaders who are narcissistic yet humble may seem oxymoronic and even paradoxical, researchers have suggested that seemingly contradictory personal attributes may exist simultaneously and may actually work together to produce positive outcomes. Results from survey data from followers and leaders working for a large health insurance organization showed that the interaction of leader narcissism and leader humility is associated with perceptions of leader effectiveness, follower job engagement, and subjective and objective follower job performance. Together, these results suggest that narcissistic leaders can have positive effects on followers when their narcissism is tempered by humility.

Integrated analyses resolve conflicts over squamate reptile phylogeny and reveal unexpected placements for fossil taxa.

Abstract: Squamate reptiles (lizards and snakes) are a pivotal group whose relationships have become increasingly controversial. Squamates include >9000 species, making them the second largest group of terrestrial vertebrates. They are important medicinally and as model systems for ecological and evolutionary research. However, studies of squamate biology are hindered by uncertainty over their relationships, and some consider squamate phylogeny unresolved, given recent conflicts between molecular and morphological results. To resolve these conflicts, we expand existing morphological and molecular datasets for squamates (691 morphological characters and 46 genes, for 161 living and 49 fossil taxa, including a new set of 81 morphological characters and adding two genes from published studies) and perform integrated analyses. Our results resolve higher-level relationships as indicated by molecular analyses, and reveal hidden morphological support for the molecular hypothesis (but not vice-versa). Furthermore, we find that integrating molecular, morphological, and paleontological data leads to surprising placements for two major fossil clades (Mosasauria and Polyglyphanodontia). These results further demonstrate the importance of combining fossil and molecular information, and the potential problems of estimating the placement of fossil taxa from morphological data alone. Thus, our results caution against estimating fossil relationships without considering relevant molecular data, and against placing fossils into molecular trees (e.g. for dating analyses) without considering the possible impact of molecular data on their placement.

Linking root traits to nutrient foraging in arbuscular mycorrhizal trees in a temperate forest

Abstract: The identification of plant functional traits that can be linked to ecosystem processes is of wide interest, especially for predicting vegetational responses to climate change Root diameter of the finest absorptive roots may be one plant trait that has wide significance Do species with relatively thick absorptive roots forage in nutrient-rich patches differently from species with relatively fine absorptive roots? We measured traits related to nutrient foraging (root morphology and architecture, root proliferation, and mycorrhizal colonization) across six coexisting arbuscular mycorrhizal (AM) temperate tree species with and without nutrient addition Root traits such as root diameter and specific root length were highly correlated with root branching intensity, with thin-root species having higher branching intensity than thick-root species In both fertilized and unfertilized soil, species with thin absorptive roots and high branching intensity showed much greater root length and mass proliferation but lower mycorrhizal colonization than species with thick absorptive roots Across all species, fertilization led to increased root proliferation and reduced mycorrhizal colonization These results suggest that thin-root species forage more by root proliferation, whereas thick-root species forage more by mycorrhizal fungi In mineral nutrient-rich patches, AM trees seem to forage more by proliferating roots than by mycorrhizal fungi

Increasing accountability through user-interface design artifacts: a new approach to addressing the problem of access-policy violations

Abstract: Access-policy violations are a growing problem with substantial costs for organizations. Although training programs and sanctions have been suggested as a means of reducing these violations, evidence shows the problem persists. It is thus imperative to identify additional ways to reduce access-policy violations, especially for systems providing broad access to data. We use accountability theory to develop four user-interface (UI) design artifacts that raise users' accountability perceptions within systems and in turn decrease access-policy violations. To test our model, we uniquely applied the scenario-based factorial survey method to various graphical manipulations of a records system containing sensitive information at a large organization with over 300 end users who use the system daily. We show that the UI design artifacts corresponding to four submanipulations of accountability can raise accountability and reduce access policy violation intentions. Our findings have several theoretical and practical implications for increasing accountability using UI design. Moreover, we are the first to extend the scenario-based factorial survey method to test design artifacts. This method provides the ability to use more design manipulations and to test with fewer users than is required in traditional experimentation and research on human--computer interaction. We also provide bootstrapping tests of mediation and moderation and demonstrate how to analyze fixed and random effects within the factorial survey method optimally.

Optical approach to resin formulation for 3D printed microfluidics

Abstract: Microfluidics imposes different requirements on 3D printing compared to many applications because the critical features for microfluidics consist of internal microvoids. Resins for general 3D printing applications, however, are not necessarily formulated to meet the requirements of microfluidics and minimize the size of fabricated voids. In this paper we use an optical approach to guide custom formulation of resins to minimize the cross sectional size of fabricated flow channels as exemplars of such voids. We focus on stereolithgraphy (SL) 3D printing with Digital Light Processing (DLP) based on a micromirror array and use a commercially available 3D printer. We develop a mathematical model for the optical dose delivered through the thickness of a 3D printed part, including the effect of voids. We find that there is a fundamental trade-off between the homogeneity of the optical dose within individual layers and how far the critical dose penetrates into a flow channel during fabrication. We also experimentally investigate the practical limits of flow channel miniaturization given the optical properties of a resin and find that the minimum flow channel height is ~3.5-5.5ha where ha is the optical penetration depth of the resin, and that the minimum width is 4 pixels in the build plane. We also show that the ratio of the build layer thickness to ha should be in the range 0.3-1.0 to obtain the minimum flow channel height for a given resin. The minimum flow channel size that we demonstrate for a custom resin is 60 μm × 108 μm for a 10 μm build layer thickness. This work lays the foundation for 3D printing of <100 μm microfluidic features.

3D printed microfluidic devices with integrated valves

Abstract: We report the successful fabrication and testing of 3D printed microfluidic devices with integrated membrane-based valves. Fabrication is performed with a low-cost commercially available stereolithographic 3D printer. Horizontal microfluidic channels with designed rectangular cross sectional dimensions as small as 350 μm wide and 250 μm tall are printed with 100% yield, as are cylindrical vertical microfluidic channels with 350 μm designed (210 μm actual) diameters. Based on our previous work [Rogers et al., Anal. Chem. 83, 6418 (2011)], we use a custom resin formulation tailored for low non-specific protein adsorption. Valves are fabricated with a membrane consisting of a single build layer. The fluid pressure required to open a closed valve is the same as the control pressure holding the valve closed. 3D printed valves are successfully demonstrated for up to 800 actuations.

Market (In)Attention and the Strategic Scheduling and Timing of Earnings Announcements

Abstract: We investigate whether managers “hide” bad news by announcing earnings during periods of low attention, or by providing less forewarning of an upcoming earnings announcement. Our findings are consistent with managers reporting bad news after market hours, on busy days, and with less advance notice, and with earnings receiving less attention in these settings. Paradoxically, our findings indicate that managers also report bad news on Fridays, but we do not find lower attention on Fridays. Further, we find negative returns when the market is notified of an upcoming Friday earnings announcement, which is consistent with investors inferring forthcoming bad news.

Effects of the microphysical Equation of State in the mergers of magnetized Neutron Stars With Neutrino Cooling

Abstract: We study the merger of binary neutron stars using different realistic, microphysical nuclear equations of state, as well as incorporating magnetic field and neutrino cooling effects. In particular, we concentrate on the influence of the equation of state on the gravitational wave signature and also on its role, in combination with cooling and electromagnetic effects, in determining the properties of the hypermassive neutron star resulting from the merger, the production of neutrinos, and the characteristics of ejecta from the system. The ejecta we find are consistent with other recent studies that find soft equations of state produce more ejecta than stiffer equations of state. Moreover, the degree of neutron richness increases for softer equations of state. In light of reported kilonova observations (associated to GRB 130603B and GRB 060614) and the discovery of relatively low abundances of heavy, radioactive elements in deep sea deposits (with respect to possible production via supernovae), we speculate that a soft equation of state (EOS) might be preferred—because of its significant production of sufficiently neutron rich ejecta—if such events are driven by binary neutron star mergers. We also find that realistic magnetic field strengths, obtained with a subgrid model tuned to capture magnetic amplification via the Kelvin-Helmholtz instability at merger, are generally too weak to affect the gravitational wave signature postmerger within a time scale of ≈10 ms but can have subtle effects on the postmerger dynamics.

A multi-institutional study of the impact of open textbook adoption on the learning outcomes of post-secondary students

Abstract: In some educational settings, the cost of textbooks approaches or even exceeds the cost of tuition. Given limited resources, it is important to better understand the impacts of free open educational resources (OER) on student outcomes. Utilizing digital resources such as OER can substantially reduce costs for students. The purpose of this study was to analyze whether the adoption of no-cost open digital textbooks significantly predicted students’ completion of courses, class achievement, and enrollment intensity during and after semesters in which OER were used. This study utilized a quantitative quasi-experimental design with propensity-score matched groups to examine differences in outcomes between students that used OER and those who did not. The demographics of the initial sample of 16,727 included 4909 students in the treatment condition with a pool of 11,818 in the control condition. There were statistically significant differences between groups, with most favoring students utilizing OER.

A roadmap for research on crassulacean acid metabolism (CAM) to enhance sustainable food and bioenergy production in a hotter, drier world.

Abstract: Crassulacean acid metabolism (CAM) is a specialized mode of photosynthesis that features nocturnal CO2 uptake, facilitates increased water-use efficiency (WUE), and enables CAM plants to inhabit water-limited environments such as semi-arid deserts or seasonally dry forests. Human population growth and global climate change now present challenges for agricultural production systems to increase food, feed, forage, fiber, and fuel production. One approach to meet these challenges is to increase reliance on CAM crops, such as Agave and Opuntia, for biomass production on semi-arid, abandoned, marginal, or degraded agricultural lands. Major research efforts are now underway to assess the productivity of CAM crop species and to harness the WUE of CAM by engineering this pathway into existing food, feed, and bioenergy crops. An improved understanding of CAM has potential for high returns on research investment. To exploit the potential of CAM crops and CAM bioengineering, it will be necessary to elucidate the evolution, genomic features, and regulatory mechanisms of CAM. Field trials and predictive models will be required to assess the productivity of CAM crops, while new synthetic biology approaches need to be developed for CAM engineering. Infrastructure will be needed for CAM model systems, field trials, mutant collections, and data management.

Alternative preprocessing of RNA-Sequencing data in The Cancer Genome Atlas leads to improved analysis results.

Abstract: Motivation: The Cancer Genome Atlas (TCGA) RNA-Sequencing data are used widely for research. TCGA provides ‘Level 3’ data, which have been processed using a pipeline specific to that resource. However, we have found using experimentally derived data that this pipeline produces gene-expression values that vary considerably across biological replicates. In addition, some RNA-Sequencing analysis tools require integer-based read counts, which are not provided with the Level 3 data. As an alternative, we have reprocessed the data for 9264 tumor and 741 normal samples across 24 cancer types using the Rsubread package. We have also collated corresponding clinical data for these samples. We provide these data as a community resource. Results: We compared TCGA samples processed using either pipeline and found that the Rsubread pipeline produced fewer zero-expression genes and more consistent expression levels across replicate samples than the TCGA pipeline. Additionally, we used a genomic-signature approach to estimate HER2 (ERBB2) activation status for 662 breast-tumor samples and found that the Rsubread data resulted in stronger predictions of HER2 pathway activity. Finally, we used data from both pipelines to classify 575 lung cancer samples based on histological type. This analysis identified various non-coding RNA that may influence lung-cancer histology. Availability and implementation: The RNA-Sequencing and clinical data can be downloaded from Gene Expression Omnibus (accession number {"type":"entrez-geo","attrs":{"text":"GSE62944","term_id":"62944"}}GSE62944). Scripts and code that were used to process and analyze the data are available from https://github.com/srp33/TCGA_RNASeq_Clinical. Contact: ude.uyb@oloccip_nehpets or ude.hatu.sciteneg@baerdna Supplementary information: Supplementary material is available at Bioinformatics online.