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bioRxiv2017

Marginal Returns And Levels Of Research Grant Support Among Scientists Supported By The National Institutes Of Health

The current era of worsening hypercompetition in biomedical research has drawn attention to the possibility of decreasing marginal returns from research funding. Recent work has described decreasing marginal returns as a function of annual dollars granted to individual scientists. However, different fields of research incur varying cost structures. Therefore, we developed a Grant Support Index (GSI) that focuses on grant activity code, as opposed to field of study or cost. In a cohort of over 71,000 unique scientists funded by NIH between 1996 and 2014 we analyzed the association of grant support (as measured by annual GSI) with 3 bibliometric outcomes, maximum Relative Citation Ratio (which arguably reflects a scientists most influential work), median Relative Citation Ratio, and annual weighted Relative Citation Ratio (which is more dependent on publication counts). We found that for all 3 measures marginal returns decline as annual GSI increases. Thus, we confirm prior findings of decreasing marginal returns with higher levels of research funding support.

scientific communication and education↗

bioRxiv2017

BioSharing: Harnessing Metadata Standards For The Data Commons

The use of community-driven metadata standards, such as minimal information guidelines, terminologies, formats/models, is essential to ensure that data and other digital research outputs are Findable, Accessible, Interoperable, and Reusable, according to the FAIR principles. As with other types of digital assets, metadata standards also need be FAIR. Their discoverability and accessibility is ensured by BioSharing, the most comprehensive resource of metadata standards, interlinked to data repositories and policies, available in the life, environmental and biomedical sciences. With its growing content, endorsements, and collaborative network, BioSharing is part of a larger ecosystem of interoperable resources. Here we describe some of the activities under the USA National Institutes of Health (NIH)s Big Data to Knowledge (BD2K) Initiative, illustrating how we track the evolution and use of metadata standards and work to connect them to indexes and annotation tools.

scientific communication and education↗

bioRxiv2017

The Reproducibility Of Research And The Misinterpretation Of P Values

We wish to answer this question If you observe a \"significant\" P value after doing a single unbiased experiment, what is the probability that your result is a false positive?. The weak evidence provided by P values between 0.01 and 0.05 is explored by exact calculations of false positive rates.\n\nWhen you observe P = 0.05, the odds in favour of there being a real effect (given by the likelihood ratio) are about 3. This is far weaker evidence than the odds of 19 to 1 that might, wrongly, be inferred from the P value. And if you want to limit the false positive rate to 5 percent, you would have to assume that you were 87% sure that there was a real effect before the experiment was done.\n\nIf you observe P = 0.001, which gives likelihood ratio of 100:1 odds on there being a real effect, that would usually be regarded as conclusive, But the false positive rate would still be 8% if the prior probability of a real effect was only 0.1\n\nDespite decades of warnings, many areas of science still insist on labelling a result of P < 0.05 as \"significant\". This must account for a substantial part of the lack of reproducibility in some areas of science. And this is before you get to the many other well-known problems, like multiple comparisons, lack of randomisation and P-hacking. Science is endangered by statistical misunderstanding, and by people who impose perverse incentives on scientists.

scientific communication and education↗

bioRxiv2017

Research Synergy and Drug Development: Bright Stars in Neighboring Constellations

Drug discovery and subsequent availability of a new breakthrough therapeutic or cure is a compelling example of societal benefit from research advances. These advances are invariably collaborative, involving the contributions of many scientists to a discovery network in which theory and experiment are built upon. To understand such scientific advances, data mining of public and commercial data sources coupled with network analysis can be used as a digital methodology to assemble and analyze component events in the history of a therapeutic. This methodology is extensible beyond the history of therapeutics and its use more generally supports (i) efficiency in exploring the scientific history of a research advance (ii) documenting and understanding collaboration (iii) portfolio analysis, planning and optimization (iv) communication of the societal value of research. As a proof of principle, we have conducted a case study of five anti-cancer therapeutics. We have linked the work of roughly 237,000 authors in 106,000 scientific publications that capture the research crucial for the development of these five therapeutics. We have enriched the content of networks of these therapeutics by annotating them with information on research awards as well as peer review that preceded these awards. Applying retrospective citation discovery, we have identified a core set of publications cited in the networks of all five therapeutics and additional intersections in combinations of networks as well as awards from the National Institutes of Health that supported this research. Lastly, we have mapped these awards to their cognate peer review panels, identifying another layer of collaborative scientific activity that influenced the research represented in these networks.

scientific communication and education↗

bioRxiv2017

Online, Interactive Tutorials Provide Effective Instruction in Science Process Skills

Explicit emphasis on teaching science process skills leads to both gains in the skills themselves and, strikingly, deeper understanding of content. Here, we created and tested a series of online, interactive tutorials with the goal of helping undergraduate students develop science process skills. We designed the tutorials in accordance with evidence-based multimedia design principles and student feedback from usability testing. We then tested the efficacy of the tutorials in an introductory undergraduate biology class. Based on a multivariate ordinary least squares regression model, students that received the tutorials are predicted to score 0.824 points higher on a 15 point science process skill assessment than their peers that received traditional textbook instruction on the same topic. This moderate but significant impact indicates that well designed online tutorials can be more effective than traditional ways of teaching science process skills to undergraduate students. We also found trends that suggest the tutorials are especially effective for non-native English speaking students. However, due to a limited sample size, we were unable to confirm that these trends occurred due to more than just variation in the sampled student group.

scientific communication and education↗

bioRxiv2017

Structural brain development: a review of methodological approaches and best practices

Continued advances in neuroimaging technologies and statistical modelling capabilities have improved our knowledge of structural brain development in children and adolescents. While this has provided an increasingly nuanced understanding of brain development, the field is still plagued by inconsistent findings. This review highlights the methodological diversity in existing longitudinal magnetic resonance imaging (MRI) studies on structural brain development during childhood and adolescence, and addresses how such variation might contribute to inconsistencies in the literature. We discuss the impact of method choices at multiple decision points across the research process, from study design and sample selection, to image processing and statistical analysis. We also highlight the extent to which different methodological considerations have been empirically examined, drawing attention to specific areas that would benefit from future investigation. Where appropriate, we recommend certain best practices that would be beneficial for the field to adopt, including greater completeness and transparency in reporting methods, in order to ultimately develop an accurate and detailed understanding of normative child and adolescent brain development.

scientific communication and education↗

bioRxiv2017

Scientific Theories and Artificial Intelligence

The grand ambition of theorists studying ecology and evolution is to discover the logical and mathematical rules driving the worlds biodiversity at every level from genetic diversity within species to differences between populations, communities, and ecosystems. This ambition has been difficult to realize in great part because of the complexity of biodiversity. Theoretical work has led to a complex web of theories, each having non-obvious consequences for other theories. Case in point, the recent realization that genetic diversity involves a great deal of temporal and spatial stochasticity forces theoretical population genetics to consider abiotic and biotic factors generally reserved to ecosystem ecology. This interconnectedness may require theoretical scientists to adopt new techniques adapted to reason about large sets of theories. Mathematicians have solved this problem by using formal languages based on logic to manage theorems. However, theories in ecology and evolution are not mathematical theorems, they involve uncertainty. Recent work in Artificial Intelligence in bridging logic and probability theory offers the opportunity to build rich knowledge bases that combine logics ability to represent complex mathematical ideas with probability theorys ability to model uncertainty. We describe these hybrid languages and explore how they could be used to build a unified knowledge base of theories for ecology and evolution.\n\ncase study you explore using the Salix tritrophic system.

scientific communication and education↗

bioRxiv2017

Bringing plants and soils to life through a simple role-playing activity

Interactions are at the core of many ecological and evolutionary forces in nature. Plant-soil interactions provide a rich example of the interconnectedness of living systems, but are hidden from everyday view and overshadowed in the classroom by more popular teaching examples involving animals, reptiles, or invertebrates. To highlight the importance and relevance of plant-soil relationships, we devised a simple role-playing activity suitable for college students. Specifically, the activity simulates how feedbacks between plants and soil environments influence plant species abundance and community richness. With this activity, students will gain a better understanding of these prolific, but overlooked, forms of biological interactions that impact the diversity and functioning of ecosystems.

scientific communication and education↗

bioRxiv2017

The GSS is an unreliable indicator of biological sciences postdoc population trends

The postdoctoral research position is an essential step on the academic career track, and the biomedical research enterprise has become heavily dependent on postdoctoral scholars to conduct experimental research. Monitoring postdoc population trends is important for crafting and evaluating policies that affect this critical population. The tool most use for understanding the trends of the biological sciences postdoc population is the Survey of Graduate Students and Postdoctorates in Science and Engineering (GSS) administered by the National Center for Science and Engineering Statistics. To determine how well institutions tracked their postdocs, we analyzed the yearly changes in the biological sciences postdoc population at institutions surveyed by the GSS from 1980 to 2015. We find examples of large changes in the biological sciences postdoc population at one or a few institutions most years from 1980 to 2015. Most universities could not explain the data presented in the GSS, and for those that provided an explanation, the most common causes were improved institutional policies and more robust tracking of their postdocs. These large changes, unrelated to hiring or layoffs, sometimes masked population trends in the broader biological sciences postdoc population. We propose the adoption of a unified definition and titles for postdocs and the creation of an index to better assess biological sciences postdoc population trends.\n\nAbbreviations

scientific communication and education↗

bioRxiv2017

Science with no fiction: measuring the veracity of scientific reports by citation analysis

The current crisis of veracity in biomedical research is enabled by the lack of publicly accessible information on whether the reported scientific claims are valid. One approach to solve this problem is to replicate previous studies by specialized reproducibility centers. However, this approach is costly or unaffordable and raises a number of yet to be resolved concerns that question its effectiveness and validity. We propose to use an approach that yields a simple numerical measure of veracity, the R-factor, by summarizing the outcomes of already published studies that have attempted to test a claim. The R-factor of an investigator, a journal, or an institution would be the average of the R-factors of the claims they reported. We illustrate this approach using three studies recently tested by a replication initiative, compare the results, and discuss how using the R-factor can help improve the veracity of scientific research.

scientific communication and education↗

bioRxiv2017

Issues in the statistical detection of data fabrication and data errors in the scientific literature: simulation study and reanalysis of Carlisle, 2017

BackgroundThe detection of fabrication or error within the scientific literature is an important and underappreciated problem. Retraction of scientific articles is rare, but retraction may also be conservative, leaving open the possiblity that many fabricated or erroneous findings remain in the literature as a result of lack of scrutiny. A recently statistical analysis of randomized controlled trials [1] has suggested that the reported statistics form these trials deviate substantially from expectation under truely random assignment, raising the possiblity of fraud or error. It has also been proposed that the method used could be implemented to prospectively screen research, for example by applying the method prior to publication.\n\nMethods and FindingsTo assess the properties of the method proposed in [1], I carry out both theoretical and empirical evaluations of the method. Simulations suggest that the method is sensitive to assumptions that could reasonably be violated in real randomized controlled trials. This suggests that deviation for expectation under this method can not be used to measure the extent of fraud or error within the literature, and raises questions about the utlity of the method for propsective screening. Empirically analysis of the results of the method on a large set of randomized trials suggests that important assumptions may plausibly be violated within this sample. Using retraction as a proxy for fraud or serious error, I show that the method faces serious challenges in terms of precision and sensitivity for the purposes of screening, and that the performance of the method as a screening tool may vary across journals and classes of retractions.\n\nConclusionsThe results in [1] should not be interpreted as indicating large amount of fraud or error within the literature. The use of this method for screening of the literature should be undertaken with great caution, and should recognize critical challenges in interpreting the results of this method.

scientific communication and education↗

bioRxiv2017

P-values and confidence intervals: not fit for purpose?

DeclarationsCompeting interests: All authors have completed theunified competing interest form and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years, no other relationships or activities that could appear to have influenced the submitted work.\n\nThe lead author (the manuscripts guarantor) affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted.\n\nEthical approval: not required\n\nDetails of funding: Not applicable\n\nStatement of independence of researchers from funders: Not applicable\n\nPatient involvement statement. Not applicable.\n\nData sharing statement: Not applicable.

scientific communication and education↗

bioRxiv2017

Findings of a retrospective, controlled cohort study of the impact of a change in Nature journals' editorial policy for life sciences research on the completeness of reporting study design and execution

ObjectiveTo determine whether a change in editorial policy, including the implementation of a checklist, has been associated with improved reporting of measures which might reduce the risk of bias.\n\nMethodsThe study protocol has been published at DOI: 10.1007/s11192-016-1964-8.\n\nDesignObservational cohort study.\n\nPopulationArticles describing research in the life sciences published in Nature journals, submitted after May 1st 2013.\n\nInterventionMandatory completion of a checklist at the point of manuscript revision.\n\nComparators(1) Articles describing research in the life sciences published in Nature journals, submitted before May 2013; (2) Similar articles in other journals matched for date and topic.\n\nPrimary OutcomeChange in proportion of Nature publications describing in vivo research published before and after May 2013 reporting the Landis 4 items (randomisation, blinding, sample size calculation, exclusions).\n\nWe included 448 NPG papers (223 published before May 2013, 225 after) identified by an individual hired by NPG for this specific task, working to a standard procedure; and an independent investigator used Pubmed Related Citations to identify 448 non-NPG papers with a similar topic and date of publication in other journals; and then redacted all publications for time sensitive information and journal name. Redacted manuscripts were assessed by 2 trained reviewers against a 74 item checklist, with discrepancies resolved by a third.\n\nResults394 NPG and 353 matching non-NPG publications described in vivo research. The number of NPG publications meeting all relevant Landis 4 criteria increased from 0/203 prior to May 2013 to 31/181 (16.4%) after (2-sample test for equality of proportions without continuity correction, X2 = 36.2, df = 1, p = 1.8 x 10-9). There was no change in the proportion of non- NPG publications meeting all relevant Landis 4 criteria (1/164 before, 1/189 after). There were more substantial improvements in the individual prevalences of reporting of randomisation, blinding, exclusions and sample size calculations for in vivo experiments, and less substantial improvements for in vitro experiments.\n\nConclusionsThere was a substantial improvement in the reporting of risks of bias in in vivo research in NPG journals following a change in editorial policy, to a level that to our knowledge has not been previously observed. However, there remain opportunities for further improvement.

scientific communication and education↗

bioRxiv2017

Enabling Precision Medicine via standard communication of NGS provenance, analysis, and results

A personalized approach based on a patients or pathogens unique genomic sequence is the foundation of precision medicine. Genomic findings must be robust and reproducible, and experimental data capture should adhere to FAIR guiding principles. Moreover, effective precision medicine requires standardized reporting that extends beyond wet lab procedures to computational methods. The BioCompute framework (https://osf.io/zm97b/) enables standardized reporting of genomic sequence data provenance, including provenance domain, usability domain, execution domain, verification kit, and error domain. This framework facilitates communication and promotes interoperability. Bioinformatics computation instances that employ the BioCompute framework are easily relayed, repeated if needed and compared by scientists, regulators, test developers, and clinicians. Easing the burden of performing the aforementioned tasks greatly extends the range of practical application. Large clinical trials, precision medicine, and regulatory submissions require a set of agreed upon standards that ensures efficient communication and documentation of genomic analyses. The BioCompute paradigm and the resulting BioCompute Objects (BCO) offer that standard, and are freely accessible as a GitHub organization (https://github.com/biocompute-objects) following the \"Open-Stand.org principles for collaborative open standards development\". By communication of high-throughput sequencing studies using a BCO, regulatory agencies (e.g., FDA), diagnostic test developers, researchers, and clinicians can expand collaboration to drive innovation in precision medicine, potentially decreasing the time and cost associated with next generation sequencing workflow exchange, reporting, and regulatory reviews.

scientific communication and education↗

bioRxiv2017

Award or Reward? Which comes first, NIH funding or research impact?

Which comes first, funding or research impact? We use causal inference to determine the direction of influence in a record of 70,000 NIH-funded investigators, which was recently released. Contrary to the basic premise of many funding policies, we find that the number of citations of an investigator determine funding levels, but not the other way around.

scientific communication and education↗

bioRxiv2017

Peer-Led Team Learning Improves Minority Student Retention in STEM Majors

The Presidents Council of Advisors on Science and Technology issued a report in 2012 calling for a drastic increase in the number of STEM graduates produced in our country over the following decade if we are to remain economically competitive globally (PCAST, 2012). The report cited the disparity between the diversity among the general public versus that of the STEM professional community and recommended measures to ensure that the women and members of underrepresented racial groups, who together comprise 70% of college graduates but only 45% of college STEM graduates, would become better represented in those fields. This call for action echoed calls by the National Academy of Sciences to expand underrepresented minority participation in STEM at the college level (NAS, 2011). In the following study, we examined whether participation in the Peer-Led Team Learning (PLTL) model in introductory biology influenced the rates of recruitment into STEM and retention in STEM for underrepresented minority (URM) students and for non-URM students. Chi-square analyses reveal that there are significant gaps in STEM recruitment and retention rates between URM and non-URM students, but when these students participate in the PLTL model, no differences in STEM recruitment or retention rates were observed. Additionally, we found that STEM retention rates were significantly improved for URM students who engaged in PLTL.

scientific communication and education↗

bioRxiv2019

Is N-Hacking Ever OK? A Simulation-based study

After an experiment has been completed, a trend may be observed that is "not quite significant". Sometimes in this situation, researchers collect more data in an effort to achieve statistical significance. Such "N-hacking" is condemned because it can lead to an excess of false positive results. I use simulations to demonstrate how N-hacking causes false positives. However, in a parameter regime relevant for many experiments, the increase in false positives is quite modest. Moreover, results obtained this way have higher Positive Predictive Value than non-incremented experiments of the same sample size and statistical power. In other words, adding a few more observations to shore up a nearly-significant result can increase the reproducibility of results, counter to some current rhetoric. Many experiments are non-confirmatory, and unplanned sample augmentation with reasonable decision rules would not cause rampant irreproducibility in that context.

scientific communication and education↗

bioRxiv2019

Science communication in online media: influence of press releases on coverage of genetics and CRISPR

New scientific discoveries are communicated through multiple channels. Publications remain essential for scientists, whereas general public relies on news articles. Numerous studies investigated the path from publications to news and identified press releases as the key factor, associating them with issues such as exaggerations, but less is known about the direct influence of press releases on subject choice or on the content of media reports. Here, a cross-sectional sample of publications related to genetics and CRISPR is assessed in three independent datasets (n = 1362 publications, n = 461 press releases). Analysis finds 92.5% (CI = 88.5-96.5) dependence of news outlets on press releases in terms of topic choice and 39-43% explicit use of passages from press releases. Publications without press releases are described by 74x fewer news outlets. Even if they come from leading journals or universities, lack of a press release leads to 8.8x less coverage. Given the high impact of press releases, their reliability is especially relevant, but the majority of them omits interest disclosures - 84.3% (CI = 80.8-87.7) of press releases did not mention existing conflicts of interest, including multiple patent applications. These results establish the major indirect and direct role of press releases in science communication via online media. In line with previous research, this dependency raises concerns about possible distortions of science coverage.

scientific communication and education↗