How to Access and Use Data From the Wisconsin Longitudinal Study

With over 27,000 analysis variables covering more than 60 years of participants’ lives, the WLS data can be overwhelming to new users who are looking for the measures they need to answer their research questions. Core WLS survey data is free and easy to download from our website. As we add new types of measures and new waves of data, we refine our data sharing methods to balance our need to make the data easily available with the need to protect the confidentiality of participants. This presentation will teach users how to access to the data files they need for their research and how to use our online documentation of survey instruments and data files. Symposium attendees will also receive a USB drive with the publicly available data and complete documentation.

MGEnrichment: A web application for microglia gene list enrichment analysis

Gene expression analysis is becoming increasingly utilized in neuro-immunology research, and there is a growing need for non-programming scientists to be able to analyze their own genomic data. MGEnrichment is a web application developed both to disseminate to the community our curated database of microglia-relevant gene lists, and to allow non-programming scientists to easily conduct statistical enrichment analysis on their gene expression data. Users can upload their own gene IDs to assess the relevance of their expression data against gene lists from other studies. We include example datasets of differentially expressed genes (DEGs) from human postmortem brain samples from Autism Spectrum Disorder (ASD) and matched controls. We demonstrate how MGEnrichment can be used to expand the interpretations of these DEG lists in terms of regulation of microglial gene expression and provide novel insights into how ASD DEGs may be implicated specifically in microglial development, microbiome responses and relationships to other neuropsychiatric disorders. This tool will be particularly useful for those working in microglia, autism spectrum disorders, and neuro-immune activation research. MGEnrichment is available at https://ciernialab.shinyapps.io/MGEnrichmentApp/ and further online documentation and datasets can be found at https://github.com/ciernialab/MGEnrichmentApp. The app is released under the GNU GPLv3 open source license.

NIfTI-MRS: A standard format for magnetic resonance spectroscopic data

Purpose: The use of multiple data formats in the MRS community currently hinders data sharing and integration. NIfTI-MRS is proposed as a standard MR spectroscopy data format, which is implemented as an extension to the neuroimaging informatics technology initiative (NIfTI) format. Using this standardised format will facilitate data sharing, ease algorithm development, and encourage the integration of MRS analysis with other imaging modalities. Methods: A file format based on the NIfTI header extension framework was designed to incorporate essential spectroscopic metadata and additional encoding dimensions. A detailed description of the specification is provided. An open-source command-line conversion program is implemented to enable conversion of single-voxel and spectroscopic imaging data to NIfTI-MRS. To provide visualisation of data in NIfTI-MRS, a dedicated plugin is implemented for FSLeyes, the FSL image viewer. Results: Alongside online documentation, ten example datasets are provided in the proposed format. In addition, minimal examples of NIfTI-MRS readers have been implemented. The conversion software, spec2nii, currently converts fourteen formats to NIfTI-MRS, including DICOM and vendor proprietary formats. Conclusion: The proposed format aims to solve the issue of multiple data formats being used in the MRS community. By providing a single conversion point, it aims to simplify the processing and analysis of MRS data, thereby lowering the barrier to use of MRS. Furthermore, it can serve as the basis for open data sharing, collaboration, and interoperability of analysis programs. It also opens possibility of greater standardisation and harmonisation. By aligning with the dominant format in neuroimaging, NIfTI-MRS enables the use of mature tools present in the imaging community, demonstrated in this work by using a dedicated imaging tool, FSLeyes, as a viewer.

ARK-BIM: Open-Source Cloud-Based HBIM Platform for Archaeology

In recent years, Historic Building Information Modelling (HBIM) methodology has strengthened the documentation and interpretation of archaeological contexts and is regarded as a breakthrough in relation to established methodologies and analyses. Change is also taking place regarding web and cloud-based solutions, and this work acknowledges the importance of cloud-based and web HBIM solutions applied to Cultural Heritage assets and archaeology. More than ever, online platforms are becoming useful services to ease data exchange and validation between collaborators and stakeholders, establishing multidisciplinary approaches. Despite the presence of different cloud-based platforms, Heritage asset documentation can hardly be managed by environments or software developed for architecture and construction design. For this reason, this project is strongly founded on four pillars: online documentation, collaboration, communication and accessibility. Cognisant of these needs, the paper is aimed at the development of a custom HBIM cloud platform for archaeology, on the basis of the BIMData open-source online environment. This platform, called ARK-BIM, can be considered a modular solution leaning on HTML, JavaScript, VueJS, XEOKIT and open-source languages.

Criminal Litigation

Criminal Litigation offers a guide to the areas of criminal litigation covered in the Legal Practice Course. Making use of realistic case studies backed up by online documentation, the text combines theory with practical considerations and encourages a focus on putting knowledge into a practical context. The volume covers all procedural and evidential issues that arise in criminal cases. The more complex areas of criminal litigation are examined using diagrams, flowcharts, and examples, while potential changes in the law are highlighted. This edition has been fully revised to reflect the most recent law and practice in all aspects of criminal litigation.

MGEnrichment: a web application for microglia gene list enrichment analysis

Gene expression analysis is becoming increasingly utilized in neuro-immunology research, and there is a growing need for non-programming scientists to be able to analyze their own genomic data. MGEnrichment is a web application developed both to disseminate to the community our curated database of microglia-relevant gene lists, and to allow non-programming scientists to easily conduct statistical enrichment analysis on their gene expression data. Users can upload their own gene IDs to assess the relevance of their expression data against gene lists from other studies. We include example datasets of differentially expressed genes (DEGs) from human postmortem brain samples from Autism Spectrum Disorder (ASD) and matched controls. We demonstrate how MGEnrichment can be used to expand the interpretations of these DEG lists in terms of regulation of microglial gene expression and provide novel insights into how ASD DEGs may be implicated specifically in microglial development, microbiome responses and relationships to other neuropsychiatric disorders. This tool will be particularly useful for those working in microglia, autism spectrum disorders, and neuro-immune activation research. MGEnrichment is available at https://ciernialab.shinyapps.io/MGEnrichmentApp/ and further online documentation and datasets can be found at https://github.com/ciernialab/MGEnrichmentApp . The app is released under the GNU GPLv3 open source license.

pyControl: Open source, Python based, hardware and software for controlling behavioural neuroscience experiments

Laboratory behavioural tasks are an essential research tool. As questions asked of behaviour and brain activity become more sophisticated, the ability to specify and run richly structured tasks becomes more important. An increasing focus on reproducibility also necessitates accurate communication of task logic to other researchers. To these ends we developed pyControl, a system of open source hardware and software for controlling behavioural experiments comprising; a simple yet flexible Python-based syntax for specifying tasks as extended state machines, hardware modules for building behavioural setups, and a graphical user interface designed for efficiently running high throughput experiments on many setups in parallel, all with extensive online documentation. These tools make it quicker, easier and cheaper to implement rich behavioural tasks at scale. As important, pyControl facilitates communication and reproducibility of behavioural experiments through a highly readable task definition syntax and self-documenting features.ResourcesDocumentation: https://pycontrol.readthedocs.ioRepositories: https://github.com/pyControlUser support: https://groups.google.com/g/pycontrol

sangeranalyseR: simple and Interactive Processing of Sanger Sequencing Data in R

sangeranalyseR is feature-rich, free, and open-source R package for processing Sanger sequencing data. It allows users to go from loading reads to saving aligned contigs in a few lines of R code by using sensible defaults for most actions. It also provides complete flexibility for determining how individual reads and contigs are processed, both at the command-line in R and via interactive Shiny applications. sangeranalyseR provides a wide range of options for all steps in Sanger processing pipelines including trimming reads, detecting secondary peaks, viewing chromatograms, detecting indels and stop codons, aligning contigs, estimating phylogenetic trees, and more. Input data can be in either ABIF or FASTA format. sangeranalyseR comes with extensive online documentation and outputs aligned and unaligned reads and contigs in FASTA format, along with detailed interactive HTML reports. sangeranalyseR supports the use of colourblind-friendly palettes for viewing alignments and chromatograms. It is released under an MIT licence and available for all platforms on Bioconductor (https://bioconductor.org/packages/sangeranalyseR) and on Github (https://github.com/roblanf/sangeranalyseR).

Flex_extract v7.1.2 – a software package to retrieve and prepare ECMWF data for use in FLEXPART

Flex_extract is an open-source software package to efficiently retrieve and prepare meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF) as input for the widely used Lagrangian particle dispersion model FLEXPART and the related trajectory model FLEXTRA. ECMWF provides a variety of data sets which differ in a number of parameters (available fields, spatial and temporal resolution, forecast start times, level types etc.). Therefore, the selection of the right data for a specific application and the settings needed to obtain them are not trivial. Consequently, the data sets which can be retrieved through flex_extract by both member-state users and public users as well as their properties are explained. Flex_extract 7.1.2 is a substantially revised version with completely restructured code, mainly written in Python 3, which is introduced with all its input and output files and an explanation of the four application modes. Software dependencies and the methods for calculating the native vertical velocity η˙, the handling of flux data and the preparation of the final FLEXPART input files are documented. Considerations for applications give guidance with respect to the selection of data sets, caveats related to the land–sea mask and orography, etc. Formal software quality-assurance methods have been applied to flex_extract. A set of unit and regression tests as well as code metric data are also supplied. A short description of the installation and usage of flex_extract is provided in the Appendix. The paper points also to an online documentation which will be kept up to date with respect to future versions.