50 research outputs found

    Setting an Optimal α That Minimizes Errors in Null Hypothesis Significance Tests

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    Null hypothesis significance testing has been under attack in recent years, partly owing to the arbitrary nature of setting α (the decision-making threshold and probability of Type I error) at a constant value, usually 0.05. If the goal of null hypothesis testing is to present conclusions in which we have the highest possible confidence, then the only logical decision-making threshold is the value that minimizes the probability (or occasionally, cost) of making errors. Setting α to minimize the combination of Type I and Type II error at a critical effect size can easily be accomplished for traditional statistical tests by calculating the α associated with the minimum average of α and β at the critical effect size. This technique also has the flexibility to incorporate prior probabilities of null and alternate hypotheses and/or relative costs of Type I and Type II errors, if known. Using an optimal α results in stronger scientific inferences because it estimates and minimizes both Type I errors and relevant Type II errors for a test. It also results in greater transparency concerning assumptions about relevant effect size(s) and the relative costs of Type I and II errors. By contrast, the use of α = 0.05 results in arbitrary decisions about what effect sizes will likely be considered significant, if real, and results in arbitrary amounts of Type II error for meaningful potential effect sizes. We cannot identify a rationale for continuing to arbitrarily use α = 0.05 for null hypothesis significance tests in any field, when it is possible to determine an optimal α

    Searching for a Stochastic Background of Gravitational Waves with LIGO

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    The Laser Interferometer Gravitational-wave Observatory (LIGO) has performed the fourth science run, S4, with significantly improved interferometer sensitivities with respect to previous runs. Using data acquired during this science run, we place a limit on the amplitude of a stochastic background of gravitational waves. For a frequency independent spectrum, the new limit is ΩGW<6.5×105\Omega_{\rm GW} < 6.5 \times 10^{-5}. This is currently the most sensitive result in the frequency range 51-150 Hz, with a factor of 13 improvement over the previous LIGO result. We discuss complementarity of the new result with other constraints on a stochastic background of gravitational waves, and we investigate implications of the new result for different models of this background.Comment: 37 pages, 16 figure

    The Tao of open science for ecology

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    The field of ecology is poised to take advantage of emerging technologies that facilitate the gathering, analyzing, and sharing of data, methods, and results. The concept of transparency at all stages of the research process, coupled with free and open access to data, code, and papers, constitutes “open science.” Despite the many benefits of an open approach to science, a number of barriers to entry exist that may prevent researchers from embracing openness in their own work. Here we describe several key shifts in mindset that underpin the transition to more open science. These shifts in mindset include thinking about data stewardship rather than data ownership, embracing transparency throughout the data life‐cycle and project duration, and accepting critique in public. Though foreign and perhaps frightening at first, these changes in thinking stand to benefit the field of ecology by fostering collegiality and broadening access to data and findings. We present an overview of tools and best practices that can enable these shifts in mindset at each stage of the research process, including tools to support data management planning and reproducible analyses, strategies for soliciting constructive feedback throughout the research process, and methods of broadening access to final research products

    Upper limit map of a background of gravitational waves

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    We searched for an anisotropic background of gravitational waves using data from the LIGO S4 science run and a method that is optimized for point sources. This is appropriate if, for example, the gravitational wave background is dominated by a small number of distinct astrophysical sources. No signal was seen. Upper limit maps were produced assuming two different power laws for the source strain power spectrum. For an f^-3 power law and using the 50 Hz to 1.8 kHz band the upper limits on the source strain power spectrum vary between 1.2e-48 Hz^-1 (100 Hz/f)^3 and 1.2e-47 Hz^-1 (100 Hz /f)^3, depending on the position in the sky. Similarly, in the case of constant strain power spectrum, the upper limits vary between 8.5e-49 Hz^-1 and 6.1e-48 Hz^-1. As a side product a limit on an isotropic background of gravitational waves was also obtained. All limits are at the 90% confidence level. Finally, as an application, we focused on the direction of Sco-X1, the closest low-mass X-ray binary. We compare the upper limit on strain amplitude obtained by this method to expectations based on the X-ray luminosity of Sco-X1.Comment: 11 pages, 9 figures, 2 table

    Upper limit map of a background of gravitational waves

    Get PDF
    We searched for an anisotropic background of gravitational waves using data from the LIGO S4 science run and a method that is optimized for point sources. This is appropriate if, for example, the gravitational wave background is dominated by a small number of distinct astrophysical sources. No signal was seen. Upper limit maps were produced assuming two different power laws for the source strain power spectrum. For an f^-3 power law and using the 50 Hz to 1.8 kHz band the upper limits on the source strain power spectrum vary between 1.2e-48 Hz^-1 (100 Hz/f)^3 and 1.2e-47 Hz^-1 (100 Hz /f)^3, depending on the position in the sky. Similarly, in the case of constant strain power spectrum, the upper limits vary between 8.5e-49 Hz^-1 and 6.1e-48 Hz^-1. As a side product a limit on an isotropic background of gravitational waves was also obtained. All limits are at the 90% confidence level. Finally, as an application, we focused on the direction of Sco-X1, the closest low-mass X-ray binary. We compare the upper limit on strain amplitude obtained by this method to expectations based on the X-ray luminosity of Sco-X1.Comment: 11 pages, 9 figures, 2 table

    Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

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    The Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis

    Insights into the Musa genome: Syntenic relationships to rice and between Musa species

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    <p>Abstract</p> <p>Background</p> <p><it>Musa </it>species (Zingiberaceae, Zingiberales) including bananas and plantains are collectively the fourth most important crop in developing countries. Knowledge concerning <it>Musa </it>genome structure and the origin of distinct cultivars has greatly increased over the last few years. Until now, however, no large-scale analyses of <it>Musa </it>genomic sequence have been conducted. This study compares genomic sequence in two <it>Musa </it>species with orthologous regions in the rice genome.</p> <p>Results</p> <p>We produced 1.4 Mb of <it>Musa </it>sequence from 13 BAC clones, annotated and analyzed them along with 4 previously sequenced BACs. The 443 predicted genes revealed that Zingiberales genes share GC content and distribution characteristics with eudicot and Poaceae genomes. Comparison with rice revealed microsynteny regions that have persisted since the divergence of the Commelinid orders Poales and Zingiberales at least 117 Mya. The previously hypothesized large-scale duplication event in the common ancestor of major cereal lineages within the Poaceae was verified. The divergence time distributions for <it>Musa</it>-Zingiber (Zingiberaceae, Zingiberales) orthologs and paralogs provide strong evidence for a large-scale duplication event in the <it>Musa </it>lineage after its divergence from the Zingiberaceae approximately 61 Mya. Comparisons of genomic regions from <it>M. acuminata </it>and <it>M. balbisiana </it>revealed highly conserved genome structure, and indicated that these genomes diverged circa 4.6 Mya.</p> <p>Conclusion</p> <p>These results point to the utility of comparative analyses between distantly-related monocot species such as rice and <it>Musa </it>for improving our understanding of monocot genome evolution. Sequencing the genome of <it>M. acuminata </it>would provide a strong foundation for comparative genomics in the monocots. In addition a genome sequence would aid genomic and genetic analyses of cultivated <it>Musa </it>polyploid genotypes in research aimed at localizing and cloning genes controlling important agronomic traits for breeding purposes.</p

    The genetic architecture of the human cerebral cortex

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    The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder
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