EnGenIUS — ENVIRONMENTAL GENOME INFORMATIONAL UTILITY SYSTEM

Short-insert shotgun sequencing approaches have been applied in recent years to environmental genomic libraries. In the case of complex multispecies microbial communities, there can be many sequence reads that are not incorporated into assemblies, and thus need to be annotated and accessible as single reads. Most existing annotation systems and genome databases accommodate assembled genomes containing contiguous gene-encoding sequences. Thus, a solution is required that can work effectively with environmental genomic annotation information to facilitate data analysis. The Environmental Genome Informational Utility System (EnGenIUS) is a comprehensive environmental genome (metagenome) research toolset that was specifically designed to accommodate the needs of large (> 250 K sequence reads) environmental genome sequencing efforts. The core EnGenIUS modules consist of a set of UNIX scripts and PHP programs used for data preprocessing, an annotation pipeline with accompanying analysis tools, two entity relational databases, and a graphical user interface. The annotation pipeline has a modular structure and can be customized to best fit input data set properties. The integrated entity relational databases store raw data and annotation analysis results. Access to the underlying databases and services is facilitated through a web-based graphical user interface. Users have the ability to browse, upload, download, and analyze preprocessed data, based on diverse search criteria. The EnGenIUS toolset was successfully tested using the Alvinella pompejana epibiont environmental genome data set, which comprises more than 300 K sequence reads. A fully browsable EnGenIUS portal is available at (access code: "guest"). The scope of this paper covers the implementation details and technical aspects of the EnGenIUS toolset.

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Highly Automated Dipole EStimation (HADES)

Computational Intelligence and Neuroscience ◽

10.1155/2011/982185 ◽

2011 ◽

Vol 2011 ◽

pp. 1-11 ◽

Cited By ~ 14

Author(s):

C. Campi ◽

A. Pascarella ◽

A. Sorrentino ◽

M. Piana

Keyword(s):

Inverse Problem ◽

User Interface ◽

Graphical User Interface ◽

Particle Filtering ◽

Synthetic Data ◽

Nonlinear Relationship ◽

Data Set ◽

Automatic Estimation ◽

Dipole Estimation ◽

Dipolar Model

Automatic estimation of current dipoles from biomagnetic data is still a problematic task. This is due not only to the ill-posedness of the inverse problem but also to two intrinsic difficulties introduced by the dipolar model: the unknown number of sources and the nonlinear relationship between the source locations and the data. Recently, we have developed a new Bayesian approach, particle filtering, based on dynamical tracking of the dipole constellation. Contrary to many dipole-based methods, particle filtering does not assume stationarity of the source configuration: the number of dipoles and their positions are estimated and updated dynamically during the course of the MEG sequence. We have now developed a Matlab-based graphical user interface, which allows nonexpert users to do automatic dipole estimation from MEG data with particle filtering. In the present paper, we describe the main features of the software and show the analysis of both a synthetic data set and an experimental dataset.

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TaxonTableTools - A comprehensive, platform-independent graphical user interface software to explore and visualise DNA metabarcoding data

ARPHA Conference Abstracts ◽

10.3897/aca.4.e64786 ◽

2021 ◽

Vol 4 ◽

Author(s):

Till-Hendrik Macher ◽

Arne Beermann ◽

Florian Leese

Keyword(s):

User Interface ◽

Graphical User Interface ◽

Distribution Patterns ◽

Assessment Tools ◽

Biological Information ◽

Distribution Data ◽

Global Biodiversity Information Facility ◽

Data Set ◽

Wide Range ◽

Dna Metabarcoding

DNA-based identification methods, such as DNA metabarcoding, are increasingly used as biodiversity assessment tools in research and environmental management. Although powerful analysis software exists to process raw data, the translation of sequence read data into biological information and downstream analyses may be difficult for end users with limited expertise in bioinformatics. Thus, the need for easy-to-use, graphical user interface (GUI) software to analyze and visualize DNA metabarcoding data is growing. Here we present TaxonTableTools (TTT), a new platform-independent GUI that aims to fill this gap by providing simple, reproducible analysis and visualization workflows. The input format of TTT is a so-called "TaXon table". This data format can easily be generated within TTT from two common file formats that can be obtained using various published DNA metabarcoding pipelines: a read table and a taxonomy table. TTT offers a wide range of processing, filtering and analysis modules. The user can analyze and visualize basic statistics, such as read proportion per taxon, as well as more sophisticated visualizations such as interactive Krona charts for taxonomic data exploration, or complex parallel category diagrams to assess species distribution patterns. Venn diagrams can be calculated to compare taxon overlap among replicates, samples, or analysis methods. Various ecological analyses can be produced directly, including alpha or beta diversity estimates, rarefaction analyses, and principal coordinate or non-metric multidimensional scaling plots. The taxonomy of a data set can be validated via the Global Biodiversity Information Facility (GBIF) API to check for synonyms and spelling mistakes. Furthermore, geographical distribution data can be automatically downloaded from GBIF. Additionally, TTT offers a conversion tool for DNA metabarcoding data into formats required for traditional, taxonomy-based analyses performed by regulatory bioassessment programs. Beyond that, TTT is able to produce fully interactive html-based graphics that can be analyzed in any web browser. The software comes with a manual and tutorial, is free and publicly available through GitHub (https://github.com/TillMacher/TaxonTableTools) or the Python package index (https://pypi.org/project/taxontabletools/).

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Transit Analysis Package: An IDL Graphical User Interface for Exoplanet Transit Photometry

Advances in Astronomy ◽

10.1155/2012/697967 ◽

2012 ◽

Vol 2012 ◽

pp. 1-8 ◽

Cited By ~ 63

Author(s):

J. Zachary Gazak ◽

John A. Johnson ◽

John Tonry ◽

Diana Dragomir ◽

Jason Eastman ◽

...

Keyword(s):

User Interface ◽

Graphical User Interface ◽

Likelihood Function ◽

Light Curves ◽

Parameter Uncertainties ◽

Data Set ◽

Specific Data ◽

Software Release ◽

Analysis Package ◽

Good Agreement

We present an IDL graphical user-interface-driven software package designed for the analysis of exoplanet transit light curves. The Transit Analysis Package (TAP) software uses Markov Chain Monte Carlo (MCMC) techniques to fit light curves using the analytic model of Mandal and Agol (2002). The package incorporates a wavelet-based likelihood function developed by Carter and Winn (2009), which allows the MCMC to assess parameter uncertainties more robustly than classicχ2methods by parameterizing uncorrelated “white” and correlated “red” noise. The software is able to simultaneously analyze multiple transits observed in different conditions (instrument, filter, weather, etc.). The graphical interface allows for the simple execution and interpretation of Bayesian MCMC analysis tailored to a user’s specific data set and has been thoroughly tested on ground-based andKeplerphotometry. This paper describes the software release and provides applications to new and existing data. Reanalysis of ground-based observations of TrES-1b, WASP-4b, and WASP-10b (Winn et al., 2007, 2009; Johnson et al., 2009; resp.) and space-basedKepler4b–8b (Kipping and Bakos 2010) show good agreement between TAP and those publications. We also present new multi-filter light curves of WASP-10b and we find excellent agreement with previously published values for a smaller radius.

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CEPS: An Open Access MATLAB Graphical User Interface (GUI) for the Analysis of Complexity and Entropy in Physiological Signals

Entropy ◽

10.3390/e23030321 ◽

2021 ◽

Vol 23 (3) ◽

pp. 321

Author(s):

David Mayor ◽

Deepak Panday ◽

Hari Kala Kandel ◽

Tony Steffert ◽

Duncan Banks

Keyword(s):

User Interface ◽

Open Access ◽

Graphical User Interface ◽

Linear Time ◽

Physiological Signals ◽

Physiological Data ◽

Data Set ◽

Convenience Sample ◽

Paced Breathing ◽

Entropy Measures

Background: We developed CEPS as an open access MATLAB® GUI (graphical user interface) for the analysis of Complexity and Entropy in Physiological Signals (CEPS), and demonstrate its use with an example data set that shows the effects of paced breathing (PB) on variability of heart, pulse and respiration rates. CEPS is also sufficiently adaptable to be used for other time series physiological data such as EEG (electroencephalography), postural sway or temperature measurements. Methods: Data were collected from a convenience sample of nine healthy adults in a pilot for a larger study investigating the effects on vagal tone of breathing paced at various different rates, part of a development programme for a home training stress reduction system. Results: The current version of CEPS focuses on those complexity and entropy measures that appear most frequently in the literature, together with some recently introduced entropy measures which may have advantages over those that are more established. Ten methods of estimating data complexity are currently included, and some 28 entropy measures. The GUI also includes a section for data pre-processing and standard ancillary methods to enable parameter estimation of embedding dimension m and time delay τ (‘tau’) where required. The software is freely available under version 3 of the GNU Lesser General Public License (LGPLv3) for non-commercial users. CEPS can be downloaded at https://bitbucket.org/deepak_panday/ceps/src/pipeline_v2/. In our illustration on PB, most complexity and entropy measures decreased significantly in response to breathing at 7 breaths per minute, differentiating more clearly than conventional linear, time- and frequency-domain measures between breathing states. In contrast, Higuchi fractal dimension increased during paced breathing. Conclusions: We have developed CEPS software as a physiological data visualiser able to integrate state of the art techniques. The interface is designed for clinical research and has a structure designed for integrating new tools. The aim is to strengthen collaboration between clinicians and the biomedical community, as demonstrated here by using CEPS to analyse various physiological responses to paced breathing.

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LDkit: a parallel computing toolkit for linkage disequilibrium analysis

BMC Bioinformatics ◽

10.1186/s12859-020-03754-5 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

You Tang ◽

Zhuo Li ◽

Chao Wang ◽

Yuxin Liu ◽

Helong Yu ◽

...

Keyword(s):

Parallel Computing ◽

Linkage Disequilibrium ◽

User Interface ◽

Graphical User Interface ◽

Demographic History ◽

Linkage Disequilibrium Analysis ◽

Genome Data ◽

Java Language ◽

Computation Process ◽

A Site

Abstract Background Linkage disequilibrium (LD) analysis is broadly utilized in genetics to understand the evolutionary and demographic history and helps geneticists identify genes associated with interested inherited traits, such as diseases. There are some tools for linkage disequilibrium analysis either in a local or online way; however, there has been no such tool supporting both graphical user interface (GUI) and parallel computing. Results We developed a GUI software called LDkit for LD analysis, which supports parallel computing. The LDkit supports both variant call format (VCF) and PLINK ‘ped + map’ format. At the same time, users could also just analyze a subset of individuals from the whole population. The LDkit reads the data by block and then paralleled the computation process by monitoring the usage of processes. Assessment on the Human 1000 genome data showed that when paralleled with 32 threads, the running time was reduced to less than 6 minutes from ~77 minutes using the chromosome 22 dataset with 1,103,547 SNPs and 2504 individuals. Conclusions The software LDkit can be effectively used to calculate and plot LD decay, LD block, and linkage disequilibrium analysis between a site and a given region. Most importantly, both graphical user interface (GUI) and stand-alone packages are available for users’ convenience. LDkit was written in JAVA language under cross-platform support.

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XDSAPP: a graphical user interface for the convenient processing of diffraction data usingXDS

Journal of Applied Crystallography ◽

10.1107/s0021889812011715 ◽

2012 ◽

Vol 45 (3) ◽

pp. 568-572 ◽

Cited By ~ 184

Author(s):

Michael Krug ◽

Manfred S. Weiss ◽

Udo Heinemann ◽

Uwe Mueller

Keyword(s):

User Interface ◽

Data Collection ◽

Data Processing ◽

Graphical User Interface ◽

Diffraction Data ◽

Easy Access ◽

Translational Symmetry ◽

Data Sets ◽

Data Set ◽

Radiation Decay

XDSAPPis a Tcl/Tk-based graphical user interface for the easy and convenient processing of diffraction data sets usingXDS. It provides easy access to allXDSfunctionalities, automates the data processing and generates graphical plots of various data set statistics provided byXDS. By incorporating additional software, further information on certain features of the data set, such as radiation decay during data collection or the presence of pseudo-translational symmetry and/or twinning, can be obtained. Intensity files suitable forCCP4,CNSandSHELXare generated.

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Graphical User Interface for Human Intervention in 2D-3D Registration of Medical Images

Volume 7A: 9th International Conference on Multibody Systems, Nonlinear Dynamics, and Control ◽

10.1115/detc2013-13659 ◽

2013 ◽

Author(s):

Grant L. S. Marchelli ◽

David R. Haynor ◽

William R. Ledoux ◽

Mark A. Ganter ◽

Duane W. Storti

Keyword(s):

User Interface ◽

Graphical User Interface ◽

3D Imaging ◽

Quality Measure ◽

Reference Image ◽

3D Registration ◽

Data Set ◽

Image Guided ◽

2D And 3D

Image-guided medical therapies and image-guided biomechanical measurement systems often combine 2D and 3D imaging modalities. Determination of relations between the 2D and 3D imaging data is known as 2D-3D registration. Motivated by an ongoing project aimed at non-invasive, marker-free measurement of the kinematics of the bones in the foot during gait, we consider a registration approach that involves (1) computing projections of the 3D data set, (2) computing a quality measure to describe the agreement/discrepancy between the simulated projections and actual 2D images, and (3) optimization of the quality measure relative to the kinematic degrees of freedom to determine the optimal registration. For our particular project, the 3D imaging modality is CT scan, the 2D modality is bi-plane fluoroscopy, the computed projection is a digitally reconstructed radiograph (DRR), the quality measure is normalized cross-correlation (NCC) between a pair of DRRs and a pair of corresponding fluoroscope images, and the 2D imaging includes a sequence of several hundred stereo image pairs. We have recently released a software toolkit, DRRACC, that accelerates both the DRR and NCC computations via GPU-based parallel processing to enable more efficient automated determination of kinematic relations for optimal registration. While fully automated 2D-3D registration is desirable, there are situations (such as creating a reasonable starting configuration for optimization, re-starting after the optimizer fails to converge, and visual verification of registration relations) when it is desirable/necessary to have a human in the loop. In this paper, we present an OpenGL-based graphical user interface that employs the DRRACC toolkit to allow the user to manipulate the kinematics of individual objects (bones) segmented from the 3D imaging and to view the corresponding DRR and the associated correlation with a reference image in real time. We also present plots showing initial results for the dependence of the registration measure on pairs of kinematic parameters. The plots show well-defined peaks that support the hope for automated registration, but they also contain large relatively flat regions that may prove problematic for gradient-based optimizers and necessitate the sort of interface presented in this paper.

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