scholarly journals MitoTrack, a user-friendly semi-automatic software for lineage tracking in living embryos

2019 ◽  
Author(s):  
A Trullo ◽  
J Dufourt ◽  
M Lagha
Keyword(s):  
Graphical User Interface ◽  
Transcriptional Activation ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Automatic Image Analysis ◽  
Lineage Tree ◽  
Automatic Software ◽  
Integrated Software ◽  
Lineage Tracking ◽  
User Friendly

Abstract Motivation During development, progenitor cells undergo multiple rounds of cellular divisions during which transcriptional programs must be faithfully propagated. Investigating the timing of transcriptional activation, which is a highly stochastic phenomenon, requires the analysis of large amounts of data. In order to perform automatic image analysis of transcriptional activation, we developed a software that segments and tracks both small and large objects, leading the user from raw data up to the results in their final form. Results MitoTrack is a user-friendly open-access integrated software that performs the specific dual task of reporting the precise timing of transcriptional activation while keeping lineage tree history for each nucleus of a living developing embryo. The software works automatically but provides the possibility to easily supervise, correct and validate each step. Availability and implementation MitoTrack is an open source Python software, embedded within a graphical user interface (download here). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals YeastSpotter: accurate and parameter-free web segmentation for microscopy images of yeast cells

2019 ◽  
Vol 35 (21) ◽  
pp. 4525-4527 ◽  
Author(s):  
Alex X Lu ◽  
Taraneh Zarin ◽  
Ian S Hsu ◽  
Alan M Moses
Keyword(s):  
Image Analysis ◽  
Web Application ◽  
Single Cells ◽  
Yeast Cells ◽  
Supplementary Information ◽  
Supplementary Data ◽  
User Friendly ◽  
Microscopy Images

Abstract Summary We introduce YeastSpotter, a web application for the segmentation of yeast microscopy images into single cells. YeastSpotter is user-friendly and generalizable, reducing the computational expertise required for this critical preprocessing step in many image analysis pipelines. Availability and implementation YeastSpotter is available at http://yeastspotter.csb.utoronto.ca/. Code is available at https://github.com/alexxijielu/yeast_segmentation. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals MetumpX—a metabolomics support package for untargeted mass spectrometry

2019 ◽  
Vol 36 (5) ◽  
pp. 1647-1648 ◽  
Author(s):  
Bilal Wajid ◽  
Hasan Iqbal ◽  
Momina Jamil ◽  
Hafsa Rafique ◽  
Faria Anwar
Keyword(s):  
Mass Spectrometry ◽  
Data Analysis ◽  
Small Molecules ◽  
Software Package ◽  
Life Sciences ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Software Packages ◽  
Develop Software ◽  
User Friendly

Abstract Motivation Metabolomics is a data analysis and interpretation field aiming to study functions of small molecules within the organism. Consequently Metabolomics requires researchers in life sciences to be comfortable in downloading, installing and scripting of software that are mostly not user friendly and lack basic GUIs. As the researchers struggle with these skills, there is a dire need to develop software packages that can automatically install software pipelines truly speeding up the learning curve to build software workstations. Therefore, this paper aims to provide MetumpX, a software package that eases in the installation of 103 software by automatically resolving their individual dependencies and also allowing the users to choose which software works best for them. Results MetumpX is a Ubuntu-based software package that facilitate easy download and installation of 103 tools spread across the standard metabolomics pipeline. As far as the authors know MetumpX is the only solution of its kind where the focus lies on automating development of software workstations. Availability and implementation https://github.com/hasaniqbal777/MetumpX-bin. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Temporal network alignment via GoT-WAVE

2019 ◽  
Vol 35 (18) ◽  
pp. 3527-3529 ◽  
Author(s):  
David Aparício ◽  
Pedro Ribeiro ◽  
Tijana Milenković ◽  
Fernando Silva
Keyword(s):  
User Interface ◽  
State Of The Art ◽  
Source Code ◽  
Network Alignment ◽  
Supplementary Information ◽  
Temporal Network ◽  
Temporal Networks ◽  
Supplementary Data ◽  
Node Similarity ◽  
User Friendly

Abstract Motivation Network alignment (NA) finds conserved regions between two networks. NA methods optimize node conservation (NC) and edge conservation. Dynamic graphlet degree vectors are a state-of-the-art dynamic NC measure, used within the fastest and most accurate NA method for temporal networks: DynaWAVE. Here, we use graphlet-orbit transitions (GoTs), a different graphlet-based measure of temporal node similarity, as a new dynamic NC measure within DynaWAVE, resulting in GoT-WAVE. Results On synthetic networks, GoT-WAVE improves DynaWAVE’s accuracy by 30% and speed by 64%. On real networks, when optimizing only dynamic NC, the methods are complementary. Furthermore, only GoT-WAVE supports directed edges. Hence, GoT-WAVE is a promising new temporal NA algorithm, which efficiently optimizes dynamic NC. We provide a user-friendly user interface and source code for GoT-WAVE. Availability and implementation http://www.dcc.fc.up.pt/got-wave/ Supplementary information Supplementary data are available at Bioinformatics online.

CellTracker (not only) for dummies

2015 ◽  
Vol 32 (6) ◽  
pp. 955-957 ◽  
Author(s):  
Filippo Piccinini ◽  
Alexa Kiss ◽  
Peter Horvath
Keyword(s):  
Graphical User Interface ◽  
Open Source Software ◽  
Phase Contrast ◽  
Cell Tracking ◽  
Source Code ◽  
Software Tool ◽  
Time Lapse ◽  
Supplementary Information ◽  
Differential Interference Contrast ◽  
User Friendly

Abstract Motivation: Time-lapse experiments play a key role in studying the dynamic behavior of cells. Single-cell tracking is one of the fundamental tools for such analyses. The vast majority of the recently introduced cell tracking methods are limited to fluorescently labeled cells. An equally important limitation is that most software cannot be effectively used by biologists without reasonable expertise in image processing. Here we present CellTracker, a user-friendly open-source software tool for tracking cells imaged with various imaging modalities, including fluorescent, phase contrast and differential interference contrast (DIC) techniques. Availability and implementation: CellTracker is written in MATLAB (The MathWorks, Inc., USA). It works with Windows, Macintosh and UNIX-based systems. Source code and graphical user interface (GUI) are freely available at: http://celltracker.website/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

scholarly journals dittoSeq: universal user-friendly single-cell and bulk RNA sequencing visualization toolkit

2020 ◽  
Author(s):  
Daniel G Bunis ◽  
Jared Andrews ◽  
Gabriela K Fragiadakis ◽  
Trevor D Burt ◽  
Marina Sirota
Keyword(s):  
Single Cell ◽  
R Package ◽  
Color Blindness ◽  
Ease Of Use ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Rnaseq Data ◽  
Visualization Toolkit ◽  
User Friendly ◽  
Publication Quality

Abstract Summary A visualization suite for major forms of bulk and single-cell RNAseq data in R. dittoSeq is color blindness-friendly by default, robustly documented to power ease-of-use and allows highly customizable generation of both daily-use and publication-quality figures. Availability and implementation dittoSeq is an R package available through Bioconductor via an open source MIT license. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Audit logs to enforce document integrity in Skyline and Panorama

2020 ◽  
Vol 36 (15) ◽  
pp. 4366-4368
Author(s):  
Tobias Rohde ◽  
Rita Chupalov ◽  
Nicholas Shulman ◽  
Vagisha Sharma ◽  
Josh Eckels ◽  
...  
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Quantitative Data ◽  
Supplementary Information ◽  
Command Line ◽  
Supplementary Data ◽  
Spectrometry Method ◽  
Quantitative Data Analysis ◽  
User Actions ◽  
Web Repository

Abstract Summary Skyline is a Windows application for targeted mass spectrometry method creation and quantitative data analysis. Like most graphical user interface (GUI) tools, it has a complex user interface with many ways for users to edit their files which makes the task of logging user actions challenging and is the reason why audit logging of every change is not common in GUI tools. We present an object comparison-based approach to audit logging for Skyline that is extensible to other GUI tools. The new audit logging system keeps track of all document modifications made through the GUI or the command line and displays them in an interactive grid. The audit log can also be uploaded and viewed in Panorama, a web repository for Skyline documents that can be configured to only accept documents with a valid audit log, based on embedded hashes to protect log integrity. This makes workflows involving Skyline and Panorama more reproducible. Availability and implementation Skyline is freely available at https://skyline.ms. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals mixtureS: a novel tool for bacterial strain genome reconstruction from reads

2020 ◽  
Author(s):  
Xin Li ◽  
Haiyan Hu ◽  
Xiaoman Li
Keyword(s):  
Environmental Samples ◽  
De Novo ◽  
Source Code ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Bacterial Strains ◽  
Metagenomic Sample ◽  
Almost All ◽  
User Friendly ◽  
Strain Genome

Abstract Motivation It is essential to study bacterial strains in environmental samples. Existing methods and tools often depend on known strains or known variations, cannot work on individual samples, not reliable, or not easy to use, etc. It is thus important to develop more user-friendly tools that can identify bacterial strains more accurately. Results We developed a new tool called mixtureS that can de novo identify bacterial strains from shotgun reads of a clonal or metagenomic sample, without prior knowledge about the strains and their variations. Tested on 243 simulated datasets and 195 experimental datasets, mixtureS reliably identified the strains, their numbers and their abundance. Compared with three tools, mixtureS showed better performance in almost all simulated datasets and the vast majority of experimental datasets. Availability and implementation The source code and tool mixtureS is available at http://www.cs.ucf.edu/˜xiaoman/mixtureS/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals SEABED: Small molEcule activity scanner weB servicE baseD

2014 ◽  
Vol 31 (5) ◽  
pp. 773-775 ◽  
Author(s):  
Carlos Fenollosa ◽  
Marcel Otón ◽  
Pau Andrio ◽  
Jorge Cortés ◽  
Modesto Orozco ◽  
...  
Keyword(s):  
Web Service ◽  
Web Server ◽  
Software As A Service ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Ensemble Docking ◽  
Web Tools ◽  
Protein Mutants ◽  
User Friendly ◽  
Hybrid Docking

Abstract Motivation: The SEABED web server integrates a variety of docking and QSAR techniques in a user-friendly environment. SEABED goes beyond the basic docking and QSAR web tools and implements extended functionalities like receptor preparation, library editing, flexible ensemble docking, hybrid docking/QSAR experiments or virtual screening on protein mutants. SEABED is not a monolithic workflow tool but Software as a Service platform. Availability and implementation: SEABED is a free web server available athttp://www.bsc.es/SEABED. No registration is required. Contact: [email protected] Supplementary information: Supplementary data are available atBioinformatics online.

scholarly journals ATLAS: Analysis Tools for Low-depth and Ancient Samples

2017 ◽  
Author(s):  
Vivian Link ◽  
Athanasios Kousathanas ◽  
Krishna Veeramah ◽  
Christian Sell ◽  
Amelie Scheu ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Ancient Dna ◽  
State Of The Art ◽  
Supplementary Information ◽  
Post Mortem ◽  
Supplementary Data ◽  
Supplementary Material ◽  
C Program ◽  
User Friendly ◽  
Proper Analysis

AbstractSummaryPost-mortem damage (PMD) obstructs the proper analysis of ancient DNA samples and can currently only be addressed by removing or down-weighting potentially damaged data. Here we present ATLAS, a suite of methods to accurately genotype and estimate genetic diversity from ancient samples, while accounting for PMD. It works directly from raw BAM files and enables the building of complete and customized pipelines for the analysis of ancient and other low-depth samples in a very user-friendly way. Based on simulations we show that, in the presence of PMD, a dedicated pipeline of ATLAS calls genotypes more accurately than the state-of-the-art pipeline of GATK combined with mapDamage 2.0.AvailabilityATLAS is an open-source C++ program freely available at https://bitbucket.org/phaentu/[email protected] informationSupplementary data are available at Bioinformatics online.

scholarly journals MutSpot: detection of non-coding mutation hotspots in cancer genomes

2019 ◽  
Author(s):  
Yu Amanda Guo ◽  
Mei Mei Chang ◽  
Anders Jacobsen Skanderup
Keyword(s):  
Somatic Mutations ◽  
R Package ◽  
Supplementary Information ◽  
Patient Specific ◽  
Supplementary Data ◽  
Link Type ◽  
Genome Wide ◽  
Cancer Genomes ◽  
User Friendly ◽  
Regulatory Dna

AbstractSummaryRecurrence and clustering of somatic mutations (hotspots) in cancer genomes may indicate positive selection and involvement in tumorigenesis. MutSpot performs genome-wide inference of mutation hotspots in non-coding and regulatory DNA of cancer genomes. MutSpot performs feature selection across hundreds of epigenetic and sequence features followed by estimation of position and patient-specific background somatic mutation probabilities. MutSpot is user-friendly, works on a standard workstation, and scales to thousands of cancer genomes.Availability and implementationMutSpot is implemented as an R package and is available at https://github.com/skandlab/MutSpot/Supplementary informationSupplementary data are available at https://github.com/skandlab/MutSpot/

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