Hierarchical cosmic shear power spectrum inference Alsing, Justin; Heavens, Alan; Jaffe, Andrew H ...
Monthly Notices of the Royal Astronomical Society,
02/2016, Letnik:
455, Številka:
4
Journal Article
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We develop a Bayesian hierarchical modelling approach for cosmic shear power spectrum inference, jointly sampling from the posterior distribution of the cosmic shear field and its (tomographic) power ...spectra. Inference of the shear power spectrum is a powerful intermediate product for a cosmic shear analysis, since it requires very few model assumptions and can be used to perform inference on a wide range of cosmological models a posteriori without loss of information. We show that joint posterior for the shear map and power spectrum can be sampled effectively by Gibbs sampling, iteratively drawing samples from the map and power spectrum, each conditional on the other. This approach neatly circumvents difficulties associated with complicated survey geometry and masks that plague frequentist power spectrum estimators, since the power spectrum inference provides prior information about the field in masked regions at every sampling step. We demonstrate this approach for inference of tomographic shear E-mode, B-mode and EB-cross power spectra from a simulated galaxy shear catalogue with a number of important features; galaxies distributed on the sky and in redshift with photometric redshift uncertainties, realistic random ellipticity noise for every galaxy and a complicated survey mask. The obtained posterior distributions for the tomographic power spectrum coefficients recover the underlying simulated power spectra for both E- and B-modes.
We present recount3, a resource consisting of over 750,000 publicly available human and mouse RNA sequencing (RNA-seq) samples uniformly processed by our new Monorail analysis pipeline. To facilitate ...access to the data, we provide the recount3 and snapcount R/Bioconductor packages as well as complementary web resources. Using these tools, data can be downloaded as study-level summaries or queried for specific exon-exon junctions, genes, samples, or other features. Monorail can be used to process local and/or private data, allowing results to be directly compared to any study in recount3. Taken together, our tools help biologists maximize the utility of publicly available RNA-seq data, especially to improve their understanding of newly collected data. recount3 is available from http://rna.recount.bio .
ABSTRACT
In this paper, we propose a Gaussian Process (GP) emulator for the calculation both of tomographic weak lensing band powers, and of coefficients of summary data massively compressed with the ...MOPED algorithm. In the former case cosmological parameter inference is accelerated by a factor of ∼10–30 compared with Boltzmann solver class applied to KiDS-450 weak lensing data. Much larger gains of order 103 will come with future data, and MOPED with GPs will be fast enough to permit the Limber approximation to be dropped, with acceleration in this case of ∼105. A potential advantage of GPs is that an error on the emulated function can be computed and this uncertainty incorporated into the likelihood. However, it is known that the GP error can be unreliable when applied to deterministic functions, and we find, using the Kullback–Leibler divergence between the emulator and class likelihoods, and from the uncertainties on the parameters, that agreement is better when the GP uncertainty is not used. In future, weak lensing surveys such as Euclid, and the Legacy Survey of Space and Time, will have up to ∼104 summary statistics, and inference will be correspondingly more challenging. However, since the speed of MOPED is determined not the number of summary data, but by the number of parameters, MOPED analysis scales almost perfectly, provided that a fast way to compute the theoretical MOPED coefficients is available. The GP provides such a fast mechanism.
Spatially-resolved transcriptomics has now enabled the quantification of high-throughput and transcriptome-wide gene expression in intact tissue while also retaining the spatial coordinates. ...Incorporating the precise spatial mapping of gene activity advances our understanding of intact tissue-specific biological processes. In order to interpret these novel spatial data types, interactive visualization tools are necessary.
We describe spatialLIBD, an R/Bioconductor package to interactively explore spatially-resolved transcriptomics data generated with the 10x Genomics Visium platform. The package contains functions to interactively access, visualize, and inspect the observed spatial gene expression data and data-driven clusters identified with supervised or unsupervised analyses, either on the user's computer or through a web application.
spatialLIBD is available at https://bioconductor.org/packages/spatialLIBD . It is fully compatible with SpatialExperiment and the Bioconductor ecosystem. Its functionality facilitates analyzing and interactively exploring spatially-resolved data from the Visium platform.
Genome-wide association studies have identified 108 schizophrenia risk loci, but biological mechanisms for individual loci are largely unknown. Using developmental, genetic and illness-based RNA ...sequencing expression analysis in human brain, we characterized the human brain transcriptome around these loci and found enrichment for developmentally regulated genes with novel examples of shifting isoform usage across pre- and postnatal life. We found widespread expression quantitative trait loci (eQTLs), including many with transcript specificity and previously unannotated sequence that were independently replicated. We leveraged this general eQTL database to show that 48.1% of risk variants for schizophrenia associate with nearby expression. We lastly found 237 genes significantly differentially expressed between patients and controls, which replicated in an independent dataset, implicated synaptic processes, and were strongly regulated in early development. These findings together offer genetics- and diagnosis-related targets for better modeling of schizophrenia risk. This resource is publicly available at http://eqtl.brainseq.org/phase1 .
Gene co-expression networks capture biological relationships between genes and are important tools in predicting gene function and understanding disease mechanisms. We show that technical and ...biological artifacts in gene expression data confound commonly used network reconstruction algorithms. We demonstrate theoretically, in simulation, and empirically, that principal component correction of gene expression measurements prior to network inference can reduce false discoveries. Using data from the GTEx project in multiple tissues, we show that this approach reduces false discoveries beyond correcting only for known confounders.
Transcription Factor 4 (TCF4) is a clinically pleiotropic gene associated with schizophrenia and Pitt-Hopkins syndrome (PTHS). To gain insight about the neurobiology of TCF4, we created an in vivo ...model of PTHS by suppressing Tcf4 expression in rat prefrontal neurons immediately prior to neurogenesis. This cell-autonomous genetic insult attenuated neuronal spiking by increasing the afterhyperpolarization. At the molecular level, using a novel technique called iTRAP that combined in utero electroporation and translating ribosome affinity purification, we identified increased translation of two ion channel genes, Kcnq1 and Scn10a. These ion channel candidates were validated by pharmacological rescue and molecular phenocopy. Remarkably, similar excitability deficits were observed in prefrontal neurons from a Tcf4+/tr mouse model of PTHS. Thus, we identify TCF4 as a regulator of neuronal intrinsic excitability in part by repression of Kcnq1 and Scn10a and suggest that this molecular function may underlie pathophysiology associated with neuropsychiatric disorders.
•TCF4 loss of function alters the intrinsic excitability of prefrontal neurons•TCF4-dependent excitability deficits are rescued by SCN10a and KCNQ1 antagonists•TCF4 represses the expression of SCN10a and KCNQ1 ion channels in central neurons•SCN10a is a potential therapeutic target for Pitt-Hopkins syndrome
Rannals et al. show that TCF4 loss of function alters the intrinsic excitability of prefrontal neurons. This excitability phenotype results from ectopic expression of two peripheral ion channels and can be rescued by acute application of antagonists.
Using a functional approach to investigate the epigenetics of type 2 diabetes (T2D), we combine three lines of evidence—diet-induced epigenetic dysregulation in mouse, epigenetic conservation in ...humans, and T2D clinical risk evidence—to identify genes implicated in T2D pathogenesis through epigenetic mechanisms related to obesity. Beginning with dietary manipulation of genetically homogeneous mice, we identify differentially DNA-methylated genomic regions. We then replicate these results in adipose samples from lean and obese patients pre- and post-Roux-en-Y gastric bypass, identifying regions where both the location and direction of methylation change are conserved. These regions overlap with 27 genetic T2D risk loci, only one of which was deemed significant by GWAS alone. Functional analysis of genes associated with these regions revealed four genes with roles in insulin resistance, demonstrating the potential general utility of this approach for complementing conventional human genetic studies by integrating cross-species epigenomics and clinical genetic risk.
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•Diet-induced obesity in mice induces widespread changes in DNA methylation•Differentially methylated regions (DMRs) are conserved in obesity and reversed by gastric bypass•The DMRs map to diabetes SNPs and adipocyte enhancers•Mouse-human experimental epigenetic approach identifies functional genes
Diet-induced obesity in mice induces epigenetic changes. Multhaup et al. show that the differentially methylated regions are conserved in human obesity and reversed by gastric bypass. They further stratified their cross-species obesity-associated regions to a large genome-wide association study for diabetes and identified four genes with roles in insulin resistance.
Highlights • Large collections of human brain tissue are prevalent in neuropsychiatric research. • Analyzing genes and their networks in the human brain can inform etiology. • Cellular composition ...should be considered in studies of homogenate brain tissue. • Methods for isolating cell populations can be powerful tools but come with caveats.
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