Tool Shed Research Articles

DANTE and DANTE_LTR: lineage-centric annotation pipelines for long terminal repeat retrotransposons in plant genomes.

Long terminal repeat (LTR) retrotransposons constitute a predominant class of repetitive DNA elements in most plant genomes. With the increasing number of sequenced plant genomes, there is an ongoing demand for computational tools facilitating efficient annotation and classification of LTR retrotransposons in plant genome assemblies. Herein, we introduce DANTE, a computational pipeline for Domain-based ANnotation of Transposable Elements, designed for sensitive detection of these elements via their conserved protein domain sequences. The identified protein domains are subsequently inputted into the DANTE_LTR pipeline to annotate complete element sequences by detecting their structural features, such as LTRs, in adjacent genomic regions. Leveraging domain sequences allows for precise classification of elements into phylogenetic lineages, offering a more granular annotation compared with coarser conventional superfamily-based classification methods. The efficiency and accuracy of this approach were evidenced via annotation of LTR retrotransposons in 93 plant genomes. Results were benchmarked against several established pipelines, showing that DANTE_LTR is capable of identifying significantly more intact LTR retrotransposons. DANTE and DANTE_LTR are provided as user-friendly Galaxy tools accessible via a public server (https://repeatexplorer-elixir.cerit-sc.cz), installable on local Galaxy instances from the Galaxy tool shed or executable from the command line.

INFLAMMATORY BOWEL DISEASE IN YOUTH UNDER 20 FROM 1990-2019: A GLOBAL PERSPECTIVE ON REGIONAL AND NATIONAL VARIATIONS FROM THE GBD 2019 ANALYSIS

Abstract BACKGROUND Inflammatory Bowel Disease (IBD) ranks as the 9th primary cause of mortality and the 10th main source of disability worldwide among individuals aged under 20. Grasping the worldwide implications for this age bracket is pivotal for shaping health care approaches and optimizing patient care. METHOD Leveraging the Global Burden of Disease instrument, we discerned the incidence, prevalence, mortality, and Disability Adjusted Life Years (DALYs) of IBD by age, gender, and year across 204 nations and territories spanning 1990-2019. The DisMod-MR 2.1 tool shed light on non-fatal health metrics like incidence and prevalence, whereas the Cause of Death Ensemble Model (CODEm) framework illuminated fatal health outcomes. RESULTS From 1990 to 2019, the overall prevalence of IBD escalated from 74,975 (95%UI: 60,678-92,219) to 88,828 (72,606-108,301), marking an Annual Percentage Change (APC) of 18% (16-22). Incidence exhibited an APC surge of 23% (20-26). Conversely, deaths and DALYs plummeted by 56% and 53% respectively during the same period. Delving into global regions, Sub-Saharan Africa noted a 6% death upswing, trailed by the African Union at 65% and Low SDI nations at 1%. Southeast Asia, East Asia, and Oceania recorded the steepest APC in age-standardized incidence rates at 67%, followed by High-SDI regions at 35%, OECD nations at 31%, and affluent countries at 30%. The 15-19 age bracket registered the most pronounced incidence rise by 24%. Males witnessed a steeper APC in incidence (24% vs. females at 21%) and prevalence (21% vs. females at 16%) from 1990-2019. CONCLUSION In 2019, IBD was responsible for 1.61% of all mortality linked to digestive diseases and contributed to 1.50% of the total digestive disease-induced disabilities. For pediatric clinicians, these findings underline the necessity for early intervention, tailored care strategies, and rigorous research into pediatric IBD. From a policy-making perspective, there is an urgent demand for resource allocation, enhanced public health campaigns, and international collaboration to mitigate the growing threat of IBD among the youth. Source: Global Burden of Disease 2019, IHME

A Review of Health Literacy Measurement Tools from the Health Literacy Tool Shed Database

A Review of Health Literacy Measurement Tools from the Health Literacy Tool Shed Database

Htseq-clip: a toolset for the preprocessing of eCLIP/iCLIP datasets.

Transcriptome-wide detection of binding sites of RNA-binding proteins is achieved using Individual-nucleotide crosslinking and immunoprecipitation (iCLIP) and its derivative enhanced CLIP (eCLIP) sequencing methods. Here, we introduce htseq-clip, a python package developed for preprocessing, extracting and summarizing crosslink site counts from i/eCLIP experimental data. The package delivers crosslink site count matrices along with other metrics, which can be directly used for filtering and downstream analyses such as the identification of differential binding sites. The Python package htseq-clip is available via pypi (python package index), bioconda and the Galaxy Tool Shed under the open source MIT License. The code is hosted at https://github.com/EMBL-Hentze-group/htseq-clip and documentation is available under https://htseq-clip.readthedocs.io/en/latest.

How the Work Gets Done

Research Article| November 01 2022 How the Work Gets Done Margaret Ann Snow Margaret Ann Snow Margaret Ann Snow is co-owner and operator of Snow’s Bend Farm. Her farm work and writing are inspired by a love of good food, a conviction to care for the land and people, a passion for plants, and a wonderment of nature. Her work has previously been published in Gravy. Search for other works by this author on: This Site PubMed Google Scholar Gastronomica (2022) 22 (4): 83–89. https://doi.org/10.1525/gfc.2022.22.4.83 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Margaret Ann Snow; How the Work Gets Done. Gastronomica 1 November 2022; 22 (4): 83–89. doi: https://doi.org/10.1525/gfc.2022.22.4.83 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentGastronomica Search Walking from the field to the tool shed, I gently twist from side to side, unkinking my spine after hours of bending over transplanting. Twenty years of farming manifest in my body, and it isn’t as forgiving as when I began. It reminds me of a young man I interviewed years ago. In the middle of the interview, he stood up to demonstrate yoga poses as an answer to my question about his qualifications. David and I tried not to laugh as he moved from triangle pose to another I didn’t recognize. Our small, organic vegetable farm in central Alabama often attracts young people in search of something. Working on a farm is seen as an experience to be had and talked about, an interesting line on a resume. Much harder to find are the people willing and able to show up every day and do the difficult work of... You do not currently have access to this content.

BioUML-towards a universal research platform.

BioUML (https://www.biouml.org)—is a web-based integrated platform for systems biology and data analysis. It supports visual modelling and construction of hierarchical biological models that allow us to construct the most complex modular models of blood pressure regulation, skeletal muscle metabolism, COVID-19 epidemiology. BioUML has been integrated with git repositories where users can store their models and other data. We have also expanded the capabilities of BioUML for data analysis and visualization of biomedical data: (i) any programs and Jupyter kernels can be plugged into the BioUML platform using Docker technology; (ii) BioUML is integrated with the Galaxy and Galaxy Tool Shed; (iii) BioUML provides two-way integration with R and Python (Jupyter notebooks): scripts can be executed on the BioUML web pages, and BioUML functions can be called from scripts; (iv) using plug-in architecture, specialized viewers and editors can be added. For example, powerful genome browsers as well as viewers for molecular 3D structure are integrated in this way; (v) BioUML supports data analyses using workflows (own format, Galaxy, CWL, BPMN, nextFlow). Using these capabilities, we have initiated a new branch of the BioUML development—u-science—a universal scientific platform that can be configured for specific research requirements.

PENERAPAN METODE KLASIFIKASI ABC DAN 5S PADA GUDANG TOOLS PT. MESIN ISUZU INDONESIA

PT.Mesin Isuzu Indonesia manufacturing industry engaged in the automotive sector which produces machinery for Isuzu products as well as several other car parts. The warehouse is a very vital place for every company, the optimal warehouse layout will support the company's production process in meeting production targets because makes it easy to get things. The potential for tool changes can not be avoided and can occur at any time, the search process for the old tool will increase maintenance time so that it is feared that the target wil not be met. This means that the layout of the tool shed must be made optimal so that when engine maintenance occurs the search process for the tool does not take much time. ABC Classification is a method for grouping based on 3 types: fast, medium, and slow. The results of this research are the layout of tools on a shelf based on ABC classification and 5S principles

PIPE-T: a new Galaxy tool for the analysis of RT-qPCR expression data

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is an accurate and fast method to measure gene expression. Reproducibility of the analyses is the main limitation of RT-qPCR experiments. Galaxy is an open, web-based, genomic workbench for a reproducible, transparent, and accessible science. Our aim was developing a new Galaxy tool for the analysis of RT-qPCR expression data. Our tool was developed using Galaxy workbench version 19.01 and functions implemented in several R packages. We developed PIPE-T, a new Galaxy tool implementing a workflow, which offers several options for parsing, filtering, normalizing, imputing, and analyzing RT-qPCR data. PIPE-T requires two input files and returns seven output files. We tested the ability of PIPE-T to analyze RT-qPCR data on two example datasets available in the gene expression omnibus repository. In both cases, our tool successfully completed execution returning expected results. PIPE-T can be easily installed from the Galaxy main tool shed or from Docker. Source code, step-by-step instructions, and example files are available on GitHub to assist new users to install, execute, and test PIPE-T. PIPE-T is a new tool suitable for the reproducible, transparent, and accessible analysis of RT-qPCR expression data.

건강정보 활용능력 활성화를 위한 선행 과제

Objectives: This study aimed to propose the necessary tasks and specific plans for activating health literacy in Korea based on international experience. Methods: This study is a qualitative research based on literature review. Helath Literacy Centre Europe, U.S. National Library of Medicine, Health Literacy Tool Shed, KISS, and RISS were searched for articles. 63 literatures that satisfied the inclusion criteria were reviewed. Results: This study suggested ‘geongang jeongbo hwalyong neunglyeog’ as the most appropriate Korean translation term for health literacy. It should be considered that inclusion of health literacy objectives in the National Health Plan 2030 and inclusion of HLS-EU16 or HLS-SF12 survey items in the Korean National Health and Nutrition Examination Survey and the Community Health Survey. Finally, the health education specialist takes charge of the health literacy work. Conclusions: In order to activate health literacy in Korea, the unification of translation terminology for health literacy, including health literacy objectives in National Health Plan, conducting health literacy surveys at the national level, and the training of professional personnel to take charge of health literacy should be given priority.

SMAGEXP: a galaxy tool suite for transcriptomics data meta-analysis

BackgroundWith the proliferation of available microarray and high-throughput sequencing experiments in the public domain, the use of meta-analysis methods increases. In these experiments, where the sample size is often limited, meta-analysis offers the possibility to considerably enhance the statistical power and give more accurate results. For those purposes, it combines either effect sizes or results of single studies in an appropriate manner. R packages metaMA and metaRNASeq perform meta-analysis on microarray and next generation sequencing (NGS) data, respectively. They are not interchangeable as they rely on statistical modeling specific to each technology.ResultsSMAGEXP (Statistical Meta-Analysis for Gene EXPression) integrates metaMA and metaRNAseq packages into Galaxy. We aim to propose a unified way to carry out meta-analysis of gene expression data, while taking care of their specificities. We have developed this tool suite to analyze microarray data from the Gene Expression Omnibus database or custom data from Affymetrix© microarrays. These data are then combined to carry out meta-analysis using metaMA package. SMAGEXP also offers to combine raw read counts from NGS experiments using DESeq2 and metaRNASeq package. In both cases, key values, independent from the technology type, are reported to judge the quality of the meta-analysis. These tools are available on the Galaxy main tool shed. A dockerized instance of galaxy containing SMAGEXP and its dependencies is available on Docker hub. Source code, help, and installation instructions are available on GitHub.ConclusionThe use of Galaxy offers an easy-to-use gene expression meta-analysis tool suite based on the metaMA and metaRNASeq packages.

QuanTP: A Software Resource for Quantitative Proteo-Transcriptomic Comparative Data Analysis and Informatics.

Next-generation sequencing technologies, coupled to advances in mass-spectrometry-based proteomics, have facilitated system-wide quantitative profiling of expressed mRNA transcripts and proteins. Proteo-transcriptomic analysis compares the relative abundance levels of transcripts and their corresponding proteins, illuminating discordant gene product responses to perturbations. These results reveal potential post-transcriptional regulation, providing researchers with important new insights into underlying biological and pathological disease mechanisms. To carry out proteo-transcriptomic analysis, researchers require software that statistically determines transcript-protein abundance correlation levels and provides results visualization and interpretation functionality, ideally within a flexible, user-friendly platform. As a solution, we have developed the QuanTP software within the Galaxy platform. The software offers a suite of tools and functionalities critical for proteo-transcriptomics, including statistical algorithms for assessing the correlation between single transcript-protein pairs as well as across two cohorts, outlier identification and clustering, along with a diverse set of results visualizations. It is compatible with analyses of results from single experiment data or from a two-cohort comparison of aggregated replicate experiments. The tool is available in the Galaxy Tool Shed through a cloud-based instance and a Docker container. In all, QuanTP provides an accessible and effective software resource, which should enable new multiomic discoveries from quantitative proteo-transcriptomic data sets.

MQC: A post-mapping data exploration tool for ribosome profiling

Background and objectiveRibosome profiling is a recent next generation sequencing technique enabling the genome-wide study of gene expression in biomedical research at the translation level. Too often, researchers precipitously start trying to test their hypotheses after alignment of their data, without checking the quality and the general features of their mapped data. Despite the fact that these checks are essential to prevent errors and ensure valid conclusions afterwards, easy-to-use tools for visualizing the quality and overall outlook of mapped ribosome profiling data are lacking. MethodsWe present mQC, a modular tool implemented as a Bioconda package and also available in the Galaxy tool shed. Herewith both bio-informaticians as well as non-experts can easily perform the indispensable visualization of both the quality and the general features of their mapped P-site corrected ribosome profiling reads. The user manual, the raw code and more information can be found on its GitHub repository (https://github.com/Biobix/mQC). ResultsmQC was tested on multiple datasets to assess its general applicability and was compared to other tools that partly perform similar tasks. ConclusionsOur results demonstrate that mQC can accomplish an unfilled but essential position in the ribosome profiling data analysis procedure by performing a thorough RIBO-Seq-specific exploration of aligned and P-site corrected ribosome profiling data.

Galaxy tool shed: tool discovery and repository management

Galaxy tool shed: tool discovery and repository management

IRProfiler \u2013 a software toolbox for high throughput immune receptor profiling

BackgroundThe study of the huge diversity of immune receptors, often referred to as immune repertoire profiling, is a prerequisite for diagnosis, prognostication and monitoring of hematological disorders. In the era of high-throughput sequencing (HTS), the abundance of immunogenetic data has revealed unprecedented opportunities for the thorough profiling of T-cell receptors (TR) and B-cell receptors (BcR). However, the volume of the data to be analyzed mandates for efficient and ease-to-use immune repertoire profiling software applications.ResultsThis work introduces Immune Repertoire Profiler (IRProfiler), a novel software pipeline that delivers a number of core receptor repertoire quantification and comparison functionalities on high-throughput TR and BcR sequencing data. Adopting 5 alternative clonotype definitions, IRProfiler implements a series of algorithms for 1) data filtering, 2) calculation of clonotype diversity and expression, 3) calculation of gene usage for the V and J subgroups, 4) detection of shared and exclusive clonotypes among multiple repertoires, and 5) comparison of gene usage for V and J subgroups among multiple repertoires. IRProfiler has been implemented as a toolbox of the Galaxy bioinformatics platform, comprising 6 tools. Theoretical and experimental evaluation has shown that the tools of IRProfiler are able to scale well with respect to the size of input dataset(s). IRProfiler has been utilized by a number of recently published studies concerning hematological disorders.ConclusionIRProfiler is made freely available via 3 distribution channels, including the Galaxy Tool Shed. Despite being a new entry in a crowded ecosystem of immune repertoire profiling software, IRProfiler founds its added value on its support for alternative clonotype definitions in conjunction with a combination of properties stemming from its user-centric design, namely ease-of-use, ease-of-access, exploitability of the output data, and analysis flexibility.

Galaxy mothur Toolset (GmT): a user-friendly application for 16S rRNA gene sequencing analysis using mothur.

BackgroundThe determination of microbial communities using the mothur tool suite (https://www.mothur.org) is well established. However, mothur requires bioinformatics-based proficiency in order to perform calculations via the command-line. Galaxy is a project dedicated to providing a user-friendly web interface for such command-line tools (https://galaxyproject.org/).ResultsWe have integrated the full set of 125+ mothur tools into Galaxy as the Galaxy mothur Toolset (GmT) and provided a set of workflows to perform end-to-end 16S rRNA gene analyses and integrate with third-party visualization and reporting tools. We demonstrate the utility of GmT by analyzing the mothur MiSeq standard operating procedure (SOP) dataset (https://www.mothur.org/wiki/MiSeq_SOP).ConclusionsGmT is available from the Galaxy Tool Shed, and a workflow definition file and full Galaxy training manual for the mothur SOP have been created. A Docker image with a fully configured GmT Galaxy is also available.

초등학교 학교 텃밭의 조성현황과 운영실태 분석: 전북지역을 중심으로

This study was conducted to investigate the set up and running status of school gardening at elementary schools in Jeollabuk-do. Among 416 elementary schools in Jeollabuk-do, 164 schools (39.4%) had school gardens. Ninety-seven schools in cities and 67 in counties had school gardens. The total area and school garden size at schools in Jeollabuk-do were 45,490 ㎡ and 277 ㎡ per school, respectively, as well as 1.6 ㎡ per students. School gardens varied in type, and percentages of outdoor and off-campus gardens were 67.2% and 17.2%, respectively. There were differences in the set up, type of garden, annual operating budget, and participants in school garden programs according to the location (city or county) of the school The installation and automation of facilities in the garden (such as greenhouse, tool shed, resource recycling facility, etc.) were poor. Most schools grew various kinds of plants, including vegetables, crops, ornamentals, and fruits. Teachers most often operated school gardens and taught students. Teachers had difficulty managing school gardens due to absence of knowledge about sustaining gardens. Most respondents reported the need for a school garden training program. Sixty-one percent of schools reported that the garden was used for academic instruction, especially during class. The majority of respondents agreed that school gardens have a positive effect and wanted to increase classes related to school gardens. Accordingly, in order to sustain school gardens and maximize their effects, systematic and customized support is needed that considers the characteristics and circumstances of the school. The facilities and features of the garden should be improved, and the school garden training program for teachers should attempt to reduce the effort required to manage the garden and increase utilization efficiency. In addition, participation of garden coordinators, parents, and community volunteers in managing gardens and implementing garden lessons is required.

CLIFinder: identification of LINE-1 chimeric transcripts in RNA-seq data.

L1 Chimeric Transcripts (LCTs) are initiated by repeated LINE-1 element antisense promoters and include the L1 5'UTR sequence in antisense orientation followed by the adjacent genomic region. LCTs have been characterized mainly using bioinformatics approaches to query dbEST. To take advantage of NGS data to unravel the transcriptome composition, we developed Chimeric LIne Finder (CLIFinder), a new bioinformatics tool. Using stranded paired-end RNA-seq data, we demonstrated that CLIFinder can identify genome-wide transcribed chimera sequences corresponding to potential LCTs. Moreover, CLIFinder can be adapted to study transcription from other repeat types. The code is available at: https://github.com/GReD-Clermont/CLIFinder; and for Galaxy users, it is directly accessible in the tool shed at: https://toolshed.g2.bx.psu.edu/view/clifinder/clifinder/. catherine.barriere@uca.fr. Supplementary data are available at Bioinformatics online.

Health Literacy Tool Shed: A Source for Validated Health Literacy Instruments

ABSTRACTAssessing patients for health literacy levels can be an important tool in effective provider-patient communication and positive health care outcomes. A number of different assessment tools are available to health care providers and researchers. The Health Literacy Tool Shed is a convenient searchable database of validated health literacy instruments. Instruments can be searched by alphabetic title list, context, domain measured, and administration time, among others. Results include a description of the tool, references, and score validation criteria. Tools may be freely available online or may be requested from the creator of the evaluation instrument.

Integration of EGA secure data access into Galaxy.

High-throughput molecular profiling techniques are routinely generating vast amounts of data for translational medicine studies. Secure access controlled systems are needed to manage, store, transfer and distribute these data due to its personally identifiable nature. The European Genome-phenome Archive (EGA) was created to facilitate access and management to long-term archival of bio-molecular data. Each data provider is responsible for ensuring a Data Access Committee is in place to grant access to data stored in the EGA. Moreover, the transfer of data during upload and download is encrypted. ELIXIR, a European research infrastructure for life-science data, initiated a project (2016 Human Data Implementation Study) to understand and document the ELIXIR requirements for secure management of controlled-access data. As part of this project, a full ecosystem was designed to connect archived raw experimental molecular profiling data with interpreted data and the computational workflows, using the CTMM Translational Research IT (CTMM-TraIT) infrastructure http://www.ctmm-trait.nl as an example. Here we present the first outcomes of this project, a framework to enable the download of EGA data to a Galaxy server in a secure way. Galaxy provides an intuitive user interface for molecular biologists and bioinformaticians to run and design data analysis workflows. More specifically, we developed a tool -- ega_download_streamer - that can download data securely from EGA into a Galaxy server, which can subsequently be further processed. This tool will allow a user within the browser to run an entire analysis containing sensitive data from EGA, and to make this analysis available for other researchers in a reproducible manner, as shown with a proof of concept study. The tool ega_download_streamer is available in the Galaxy tool shed: https://toolshed.g2.bx.psu.edu/view/yhoogstrate/ega_download_streamer.

Colib'read on galaxy: a tools suite dedicated to biological information extraction from raw NGS reads.

BackgroundWith next-generation sequencing (NGS) technologies, the life sciences face a deluge of raw data. Classical analysis processes for such data often begin with an assembly step, needing large amounts of computing resources, and potentially removing or modifying parts of the biological information contained in the data. Our approach proposes to focus directly on biological questions, by considering raw unassembled NGS data, through a suite of six command-line tools.FindingsDedicated to ‘whole-genome assembly-free’ treatments, the Colib’read tools suite uses optimized algorithms for various analyses of NGS datasets, such as variant calling or read set comparisons. Based on the use of a de Bruijn graph and bloom filter, such analyses can be performed in a few hours, using small amounts of memory. Applications using real data demonstrate the good accuracy of these tools compared to classical approaches. To facilitate data analysis and tools dissemination, we developed Galaxy tools and tool shed repositories.ConclusionsWith the Colib’read Galaxy tools suite, we enable a broad range of life scientists to analyze raw NGS data. More importantly, our approach allows the maximum biological information to be retained in the data, and uses a very low memory footprint.Electronic supplementary materialThe online version of this article (doi:10.1186/s13742-015-0105-2) contains supplementary material, which is available to authorized users.