Female grant applicants are equally successful when peer reviewers assess the science, but not when they assess the scientist, bioRxiv, 2017-12-13
ABSTRACTBackgroundPrevious research shows that men often receive more research funding than women, but does not provide empirical evidence as to why this occurs. In 2014, the Canadian Institutes of Health Research (CIHR) created a natural experiment by dividing all investigator-initiated funding into two new grant programs one with and one without an explicit review focus on the caliber of the principal investigator.MethodsWe analyzed application success among 23,918 grant applications from 7,093 unique principal investigators in a 5-year natural experiment across all investigator-initiated CIHR grant programs in 2011-2016. We used Generalized Estimating Equations to account for multiple applications by the same applicant and an interaction term between each principal investigator’s self-reported sex and grant programs to compare success rates between male and female applicants under different review criteria.ResultsThe overall grant success rate across all competitions was 15.8%. After adjusting for age and research domain, the predicted probability of funding success in traditional programs was 0.9 percentage points higher for male than for female principal investigators (OR 0.934, 95% CI 0.854-1.022). In the new program focused on the proposed science, the gap was 0.9 percentage points in favour of male principal investigators (OR 0.998, 95% CI 0.794-1.229). In the new program with an explicit review focus on the caliber of the principal investigator, the gap was 4.0 percentage points in favour of male principal investigators (OR 0.705, 95% CI 0.519- 0.960).InterpretationThis study suggests gender gaps in grant funding are attributable to less favourable assessments of women as principal investigators, not differences in assessments of the quality of science led by women. We propose ways for funders to avoid allowing gender bias to influence research funding.FundingThis study was unfunded.
biorxiv scientific-communication-and-education 500+-users 2017Pathway enrichment analysis of -omics data, bioRxiv, 2017-12-13
ABSTRACTPathway enrichment analysis helps gain mechanistic insight into large gene lists typically resulting from genome scale (–omics) experiments. It identifies biological pathways that are enriched in the gene list more than expected by chance. We explain pathway enrichment analysis and present a practical step-by-step guide to help interpret gene lists resulting from RNA-seq and genome sequencing experiments. The protocol comprises three major steps define a gene list from genome scale data, determine statistically enriched pathways, and visualize and interpret the results. We focus on differentially expressed genes and mutated cancer genes, however the described principles can be applied to diverse –omics data. The protocol is designed for biologists with no prior bioinformatics training and uses freely available software including gProfiler, GSEA, Cytoscape and Enrichment Map.
biorxiv bioinformatics 100-200-users 2017Rarefaction, alpha diversity, and statistics, bioRxiv, 2017-12-12
AbstractUnderstanding the drivers of microbial diversity is a fundamental question in microbial ecology. Extensive literature discusses different methods for describing microbial diversity and documenting its effects on ecosystem function. However, it is widely believed that diversity depends on the number of reads that are sequenced. I discuss a statistical perspective on diversity, framing the diversity of an environment as an unknown parameter, and discussing the bias and variance of plug-in and rarefied estimates. I argue that by failing to account for both bias and variance, we invalidate analysis of alpha diversity. I describe the state of the statistical literature for addressing these problems, and suggest that measurement error modeling can address issues with variance, but bias corrections need to be utilized as well. I encourage microbial ecologists to avoid motivating their investigations with alpha diversity analyses that do not use valid statistical methodology.
biorxiv microbiology 0-100-users 2017Robust manipulation of the behavior of Drosophila melanogaster by a fungal pathogen in the laboratory, bioRxiv, 2017-12-11
AbstractMany microbes induce striking behavioral changes in their animal hosts, but how they achieve this is poorly understood, especially at the molecular level. Mechanistic understanding has been largely constrained by the lack of a model system with advanced tools for molecular manipulation. We recently discovered a strain of the behavior-manipulating fungal pathogen Entomophthora muscae infecting wild Drosophila, and established methods to infect D. melanogaster in the lab. Lab-infected flies manifest the moribund behaviors characteristic of E. muscae infection hours before death, they climb upward, extend their proboscides and affix in place, then raise their wings, clearing a path for infectious spores to launch from their abdomens. We found that E. muscae invades the fly nervous system, suggesting a direct means by which the fungus could induce behavioral changes. Given the vast molecular toolkit available for D. melanogaster, we believe this new system will enable rapid progress in understanding the mechanistic basis of E. muscae’s behavioral manipulation in the fly.
biorxiv animal-behavior-and-cognition 200-500-users 2017The ancestral animal genetic toolkit revealed by diverse choanoflagellate transcriptomes, bioRxiv, 2017-12-11
AbstractThe changes in gene content that preceded the origin of animals can be reconstructed by comparison with their sister group, the choanoflagellates. However, only two choanoflagellate genomes are currently available, providing poor coverage of their diversity. We sequenced transcriptomes of 19 additional choanoflagellate species to produce a comprehensive reconstruction of the gains and losses that shaped the ancestral animal gene repertoire. We find roughly 1,700 gene families with origins on the animal stem lineage, of which only a core set of 36 are conserved across animals. We find more than 350 gene families that were previously thought to be animal-specific actually evolved before the animal-choanoflagellate divergence, including Notch and Delta, Toll-like receptors, and glycosaminoglycan hydrolases that regulate animal extracellular matrix (ECM). In the choanoflagellate Salpingoeca helianthica, we show that a glycosaminoglycan hydrolase modulates rosette colony size, suggesting a link between ECM regulation and morphogenesis in choanoflagellates and animals.Data AvailabilityRaw sequencing reads NCBI BioProject PRJNA419411 (19 choanoflagellate transcriptomes), PRJNA420352 (S. rosetta polyA selection test)Transcriptome assemblies, annotations, and gene families <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpsdx.doi.org10.6084m9.figshare.5686984>httpsdx.doi.org10.6084m9.figshare.5686984<jatsext-link>Protocols <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpsdx.doi.org10.17504protocols.io.kwscxee>httpsdx.doi.org10.17504protocols.io.kwscxee<jatsext-link>
biorxiv evolutionary-biology 100-200-users 2017Optogenetic dissection of descending behavioral control in Drosophila, bioRxiv, 2017-12-10
AbstractIn most animals, the brain makes behavioral decisions that are transmitted by descending neurons to the nerve cord circuitry that produces behaviors. In insects, only a few descending neurons have been associated with specific behaviors. To explore how these neurons control an insect’s movements, we developed a novel method to systematically assay the behavioral effects of activating individual neurons on freely behaving terrestrial D. melanogaster. We calculated a two-dimensional representation of the entire behavior space explored by these flies and associated descending neurons with specific behaviors by identifying regions of this space that were visited with increased frequency during optogenetic activation. Applying this approach across a population of descending neurons, we found, that (1) activation of most of the descending neurons drove stereotyped behaviors, (2) in many cases multiple descending neurons activated similar behaviors, and (3) optogenetically-activated behaviors were often dependent on the behavioral state prior to activation.
biorxiv neuroscience 0-100-users 2017