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Mastering Hyper-V 2012 R2 with System Center and Windows Azure
This book will help you understand the capabilities of Microsoft Hyper-V, architect a Hyper-V solution for your datacenter, plan a deployment/migration, and then manage it all using native tools and System Center.
eBook
Introducing Microsoft Flow : automating workflows between apps and services
\"Use Microsoft Flow in your business to improve productivity through automation with this step-by-step introductory text ... You'll see the prerequisites to get started with this cloud-based service, including how to create a flow and how to use different connectors. [It] takes you through connecting with SharePoint, creating approval flows, and using mobile apps. ... The second half of the book continues with managing connections and gateways, where you'll cover the configuration, creation,, and deletion of connectors and how to connect to a data gateway. The final topic is Flow administration and techniques to manage the environment.\"--Back cover.
Book
Visualization in Bayesian workflow
Bayesian data analysis is about more than just computing a posterior distribution, and Bayesian visualization is about more than trace plots of Markov chains. Practical Bayesian data analysis, like all data analysis, is an iterative process of model building, inference, model checking and evaluation, and model expansion. Visualization is helpful in each of these stages of the Bayesian workflow and it is indispensable when drawing inferences from the types of modern, high dimensional models that are used by applied researchers.
Journal Article
patRoon: open source software platform for environmental mass spectrometry based non-target screening
Mass spectrometry based non-target analysis is increasingly adopted in environmental sciences to screen and identify numerous chemicals simultaneously in highly complex samples. However, current data processing software either lack functionality for environmental sciences, solve only part of the workflow, are not openly available and/or are restricted in input data formats. In this paper we present
patRoon
, a new
R
based open-source software platform, which provides comprehensive, fully tailored and straightforward non-target analysis workflows. This platform makes the use, evaluation and mixing of well-tested algorithms seamless by harmonizing various common (primarily open) software tools under a consistent interface. In addition,
patRoon
offers various functionality and strategies to simplify and perform automated processing of complex (environmental) data effectively.
patRoon
implements several effective optimization strategies to significantly reduce computational times. The ability of
patRoon
to perform time-efficient and automated non-target data annotation of environmental samples is demonstrated with a simple and reproducible workflow using open-access data of spiked samples from a drinking water treatment plant study. In addition, the ability to easily use, combine and evaluate different algorithms was demonstrated for three commonly used feature finding algorithms. This article, combined with already published works, demonstrate that
patRoon
helps make comprehensive (environmental) non-target analysis readily accessible to a wider community of researchers.
Journal Article
landscapemetrics: an open‐source R tool to calculate landscape metrics
Quantifying landscape characteristics and linking them to ecological processes is one of the central goals of landscape ecology. Landscape metrics are a widely used tool for the analysis of patch‐based, discrete land‐cover classes. Existing software to calculate landscape metrics has several constraints, such as being limited to a single platform, not being open‐source or involving a complicated integration into large workflows. We present landscapemetrics, an open‐source R package that overcomes many constraints of existing landscape metric software. The package includes an extensive collection of commonly used landscape metrics in a tidy workflow. To facilitate the integration into large workflows, landscapemetrics is based on a well‐established spatial framework in R. This allows pre‐processing of land‐cover maps or further statistical analysis without importing and exporting the data from and to different software environments. Additionally, the package provides many utility functions to visualize, extract, and sample landscape metrics. Lastly, we provide building‐blocks to motivate the development and integration of new metrics in the future. We demonstrate the usage and advantages of landscapemetrics by analysing the influence of different sampling schemes on the estimation of landscape metrics. In so doing, we demonstrate the many advantages of the package, especially its easy integration into large workflows. These new developments should help with the integration of landscape analysis in ecological research, given that ecologists are increasingly using R for the statistical analysis, modelling and visualization of spatial data.
Journal Article
SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis
Background
Comparing the composition of microbial communities among groups of interest (e.g., patients vs healthy individuals) is a central aspect in microbiome research. It typically involves sequencing, data processing, statistical analysis and graphical display. Such an analysis is normally obtained by using a set of different applications that require specific expertise for installation, data processing and in some cases, programming skills.
Results
Here, we present SHAMAN, an interactive web application we developed in order to facilitate the use of (i) a bioinformatic workflow for metataxonomic analysis, (ii) a reliable statistical modelling and (iii) to provide the largest panel of interactive visualizations among the applications that are currently available. SHAMAN is specifically designed for non-expert users. A strong benefit is to use an integrated version of the different analytic steps underlying a proper metagenomic analysis. The application is freely accessible at
http://shaman.pasteur.fr/
, and may also work as a standalone application with a Docker container (aghozlane/shaman), conda and R. The source code is written in R and is available at
https://github.com/aghozlane/shaman
. Using two different datasets (a mock community sequencing and a published 16S rRNA metagenomic data), we illustrate the strengths of SHAMAN in quickly performing a complete metataxonomic analysis.
Conclusions
With SHAMAN, we aim at providing the scientific community with a platform that simplifies reproducible quantitative analysis of metagenomic data.
Journal Article
ONTbarcoder and MinION barcodes aid biodiversity discovery and identification by everyone, for everyone
Background
DNA barcodes are a useful tool for discovering, understanding, and monitoring biodiversity which are critical tasks at a time of rapid biodiversity loss. However, widespread adoption of barcodes requires cost-effective and simple barcoding methods. We here present a workflow that satisfies these conditions. It was developed via “innovation through subtraction” and thus requires minimal lab equipment, can be learned within days, reduces the barcode sequencing cost to < 10 cents, and allows fast turnaround from specimen to sequence by using the portable MinION sequencer.
Results
We describe how tagged amplicons can be obtained and sequenced with the real-time MinION sequencer in many settings (field stations, biodiversity labs, citizen science labs, schools). We also provide amplicon coverage recommendations that are based on several runs of the latest generation of MinION flow cells (“R10.3”) which suggest that each run can generate barcodes for > 10,000 specimens. Next, we present a novel software, ONTbarcoder, which overcomes the bioinformatics challenges posed by MinION reads. The software is compatible with Windows 10, Macintosh, and Linux, has a graphical user interface (GUI), and can generate thousands of barcodes on a standard laptop within hours based on only two input files (FASTQ, demultiplexing file). We document that MinION barcodes are virtually identical to Sanger and Illumina barcodes for the same specimens (> 99.99%) and provide evidence that MinION flow cells and reads have improved rapidly since 2018.
Conclusions
We propose that barcoding with MinION is the way forward for government agencies, universities, museums, and schools because it combines low consumable and capital cost with scalability. Small projects can use the flow cell dongle (“Flongle”) while large projects can rely on MinION flow cells that can be stopped and re-used after collecting sufficient data for a given project.
Journal Article
A cross-linking/mass spectrometry workflow based on MS-cleavable cross-linkers and the MeroX software for studying protein structures and protein–protein interactions
Chemical cross-linking in combination with mass spectrometric analysis of the created cross-linked products is an emerging technology aimed at deriving valuable structural information from proteins and protein complexes. The goal of our protocol is to obtain distance constraints for structure determination of proteins and to investigate protein–protein interactions. We present an integrated workflow for cross-linking/mass spectrometry (MS) based on protein cross-linking with MS-cleavable reagents, followed by enzymatic digestion, enrichment of cross-linked peptides by strong cation-exchange chromatography (SCX), and LC/MS/MS analysis. To exploit the full potential of MS-cleavable cross-linkers, we developed an updated version of the freely available MeroX software for automated data analysis. The commercially available, MS-cleavable cross-linkers (DSBU and CDI) used herein possess different lengths and react with amine as well as hydroxy groups. Owing to the formation of two characteristic 26-u doublets in their MS/MS spectra, many fewer false positives are found than when using classic, non-cleavable cross-linkers. The protocol, exemplified herein for BSA and the whole Escherichia coli ribosome, is robust and widely applicable, and it allows facile identification of cross-links for deriving spatial constraints from purified proteins and protein complexes. The cross-linking/MS procedure takes 2–3 days to complete.
Journal Article
Digital postprocessing and image segmentation for objective analysis of colorimetric reactions
Recently, there has been an explosion of scientific literature describing the use of colorimetry for monitoring the progression or the endpoint result of colorimetric reactions. The availability of inexpensive imaging technology (e.g., scanners, Raspberry Pi, smartphones and other sub-$50 digital cameras) has lowered the barrier to accessing cost-efficient, objective detection methodologies. However, to exploit these imaging devices as low-cost colorimetric detectors, it is paramount that they interface with flexible software that is capable of image segmentation and probing a variety of color spaces (RGB, HSB, Y’UV, L*a*b*, etc.). Development of tailor-made software (e.g., smartphone applications) for advanced image analysis requires complex, custom-written processing algorithms, advanced computer programming knowledge and/or expertise in physics, mathematics, pattern recognition and computer vision and learning. Freeware programs, such as ImageJ, offer an alternative, affordable path to robust image analysis. Here we describe a protocol that uses the ImageJ program to process images of colorimetric experiments. In practice, this protocol consists of three distinct workflow options. This protocol is accessible to uninitiated users with little experience in image processing or color science and does not require fluorescence signals, expensive imaging equipment or custom-written algorithms. We anticipate that total analysis time per region of interest is ~6 min for new users and <3 min for experienced users, although initial color threshold determination might take longer.
This protocol provides ImageJ-based workflows for the analysis of images obtained from colorimetric assays. New users can take advantage of a basic workflow; more experienced users can benefit from more advanced analysis procedures.
Journal Article