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Summary EpiCompare combines a variety of downstream analysis tools to compare, quality control and benchmark different epigenomic datasets. The package requires minimal input from users, can be run with just one line of code and provides all results of the analysis in a single interactive HTML report. EpiCompare thus enables downstream analysis of multiple epigenomic datasets in a simple, effective and user-friendly manner. Availability and implementation EpiCompare is available on Bioconductor (≥ v3.15): https://bioconductor.org/packages/release/bioc/html/EpiCompare.html ; all source code is publicly available via GitHub: https://github.com/neurogenomics/EpiCompare ; documentation website https://neurogenomics.github.io/EpiCompare ; and EpiCompare DockerHub repository: https://hub.docker.com/repository/docker/neurogenomicslab/epicompare. [ABSTRACT FROM AUTHOR]

Summary echolocatoR integrates a diverse suite of statistical and functional fine-mapping tools to identify, test enrichment in, and visualize high-confidence causal consensus variants in any phenotype. It requires minimal input from users (a summary statistics file), can be run in a single R function, and provides extensive access to relevant datasets (e.g. reference linkage disequilibrium panels, quantitative trait loci, genome-wide annotations, cell-type-specific epigenomics), thereby enabling rapid, robust and scalable end-to-end fine-mapping investigations. Availability and implementation echolocatoR is an open-source R package available through GitHub under the GNU General Public License (Version 3) license: https://github.com/RajLabMSSM/echolocatoR. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Motivation Genome‐wide association studies (GWAS) summary statistics have popularized and accelerated genetic research. However, a lack of standardization of the file formats used has proven problematic when running secondary analysis tools or performing meta-analysis studies. Results To address this issue, we have developed MungeSumstats, a Bioconductor R package for the standardization and quality control of GWAS summary statistics. MungeSumstats can handle the most common summary statistic formats, including variant call format (VCF) producing a reformatted, standardized, tabular summary statistic file, VCF or R native data object. Availability and implementation MungeSumstats is available on Bioconductor (v 3.13) and can also be found on Github at: https://neurogenomics.github.io/MungeSumstats. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

The hippocampal complex (HC) is central to long‐term memory storage and retrieval as well as spatial navigation across many species. Notably, humans appear to have greatly enhanced and possibly unique HC‐mediated capacities such as constructive episodic simulation. Key studies have shown that the human HC is disproportionately large amongst hominoids, but much remains unknown at the levels of substructural evolutionary reorganization and ecological selection. Here, we calculated relative sizes of 12 HC subregions in a diverse sample of 44 primate species. We then used a Bayesian phylogenetic method, selective regime analysis, to identify 27 separate evolutionary shifts in HC organization across 65 million years of primate evolution. Additionally, a series of multivariate phylogenetic regressions using HC‐related ecological variables as predictors (Diet Breadth, Population Density, Group Size, Home Range Size, and Residual Home Range) revealed that relative fascia dentata and CA1 size were both significantly predicted by species' home range size (after correcting for body size). However, perhaps the most notable finding of this study was that the shifts in HC size and subregional organization in the human lineage were the largest seen in all of primate evolution, rendering modern humans with a HC that is a clear outlier amongst all nonhuman primates investigated here. Given the extensive literature confirming the relationship between HC organization and function, these selective shifts are likely to have played a significant role in the emergence of human‐specific capacities, such as constructive episodic simulation. [ABSTRACT FROM AUTHOR]

Recent human genetic studies suggest that cells of the innate immune system have a primary role in the pathogenesis of neurodegenerative diseases. However, the results from these studies often do not elucidate how the genetic variants affect the biology of these cells to modulate disease risk. Here, we applied a tensor decomposition method to uncover disease associated gene networks linked to distal genetic variation in stimulated human monocytes and macrophages gene expression profiles. We report robust evidence that some disease associated genetic variants affect the expression of multiple genes in trans. These include a Parkinson's disease locus influencing the expression of genes mediated by a protease that controls lysosomal function, and Alzheimer's disease loci influencing the expression of genes involved in type 1 interferon signaling, myeloid phagocytosis, and complement cascade pathways. Overall, we uncover gene networks in induced innate immune cells linked to disease associated genetic variants, which may help elucidate the underlying biology of disease. Author summary: A steadily growing number of studies have identified and characterized cis expression quantitative trait loci (eQTLs) in human primary cells and tissues. However, identifying distal regulation on gene expression (trans-eQTLs) is far more difficult to detect due to smaller effect sizes and the large number of tests for thousands of transcripts. Here we applied a novel method to uncover gene networks linked to distal genetic variation (trans-eQTLs) in gene expression datasets from peripheral monocytes at baseline and stimulated with interferon (IFN) or lipopolysaccharide (LPS). We report robust evidence that some neurodegenerative disease-associated variants affect the expression of multiple genes in trans. These innate immune networks illuminate potential biological mechanisms underlying Alzheimer's and Parkinson's disease. These findings provide new insights into understanding the effect of genetic variants on gene networks contributing to disease, and may help in elucidating the molecular mechanisms of neurodegenerative diseases. [ABSTRACT FROM AUTHOR]