CoRC: the COPASI R Connector

Author(s):  
Jonas Förster ◽  
Frank T Bergmann ◽  
Jürgen Pahle

Abstract Motivation COPASI is a biochemical simulator and model analyzer which has found widespread use in academic research, teaching and beyond. One of COPASI’s strengths is its graphical user interface, and this is what most users work with. COPASI also provides a command-line tool. So far, an intuitive scripting interface that allows the creation and documentation of systems biology workflows was missing though. Results We have developed CoRC, the COPASI R Connector, an R package which provides a high-level scripting interface for COPASI. It closely mirrors the thought process of a (graphical interface) user and should therefore be very easy to use. This allows for complex workflows to be reproducibly scripted, utilizing COPASI’s powerful analytic toolset in combination with R’s extensive analysis and package ecosystem. Availability and implementation CoRC is a free and open-source R package, available via GitHub at https://jpahle.github.io/CoRC/ under the Artistic-2.0 license.   Supplementary information: We provide tutorial articles as well as several example scripts on the project’s website.

2020 ◽  
Vol 36 (10) ◽  
pp. 3263-3265 ◽  
Author(s):  
Lucas Czech ◽  
Pierre Barbera ◽  
Alexandros Stamatakis

Abstract Summary We present genesis, a library for working with phylogenetic data, and gappa, an accompanying command-line tool for conducting typical analyses on such data. The tools target phylogenetic trees and phylogenetic placements, sequences, taxonomies and other relevant data types, offer high-level simplicity as well as low-level customizability, and are computationally efficient, well-tested and field-proven. Availability and implementation Both genesis and gappa are written in modern C++11, and are freely available under GPLv3 at http://github.com/lczech/genesis and http://github.com/lczech/gappa. Supplementary information Supplementary data are available at Bioinformatics online.


2015 ◽  
Vol 14 ◽  
pp. CIN.S26470 ◽  
Author(s):  
Richard P. Finney ◽  
Qing-Rong Chen ◽  
Cu V. Nguyen ◽  
Chih Hao Hsu ◽  
Chunhua Yan ◽  
...  

The name Alview is a contraction of the term Alignment Viewer. Alview is a compiled to native architecture software tool for visualizing the alignment of sequencing data. Inputs are files of short-read sequences aligned to a reference genome in the SAM/BAM format and files containing reference genome data. Outputs are visualizations of these aligned short reads. Alview is written in portable C with optional graphical user interface (GUI) code written in C, C++, and Objective-C. The application can run in three different ways: as a web server, as a command line tool, or as a native, GUI program. Alview is compatible with Microsoft Windows, Linux, and Apple OS X. It is available as a web demo at https://cgwb.nci.nih.gov/cgi-bin/alview . The source code and Windows/Mac/Linux executables are available via https://github.com/NCIP/alview .


2019 ◽  
Vol 35 (21) ◽  
pp. 4405-4407 ◽  
Author(s):  
Steven Monger ◽  
Michael Troup ◽  
Eddie Ip ◽  
Sally L Dunwoodie ◽  
Eleni Giannoulatou

Abstract Motivation In silico prediction tools are essential for identifying variants which create or disrupt cis-splicing motifs. However, there are limited options for genome-scale discovery of splice-altering variants. Results We have developed Spliceogen, a highly scalable pipeline integrating predictions from some of the individually best performing models for splice motif prediction: MaxEntScan, GeneSplicer, ESRseq and Branchpointer. Availability and implementation Spliceogen is available as a command line tool which accepts VCF/BED inputs and handles both single nucleotide variants (SNVs) and indels (https://github.com/VCCRI/Spliceogen). SNV databases with prediction scores are also available, covering all possible SNVs at all genomic positions within all Gencode-annotated multi-exon transcripts. Supplementary information Supplementary data are available at Bioinformatics online.


2020 ◽  
Vol 36 (9) ◽  
pp. 2934-2935 ◽  
Author(s):  
Yi Zheng ◽  
Fangqing Zhao

Abstract Summary Circular RNAs (circRNAs) are proved to have unique compositions and splicing events distinct from canonical mRNAs. However, there is no visualization tool designed for the exploration of complex splicing patterns in circRNA transcriptomes. Here, we present CIRI-vis, a Java command-line tool for quantifying and visualizing circRNAs by integrating the alignments and junctions of circular transcripts. CIRI-vis can be applied to visualize the internal structure and isoform abundance of circRNAs and perform circRNA transcriptome comparison across multiple samples. Availability and implementation https://sourceforge.net/projects/ciri/files/CIRI-vis. Supplementary information Supplementary data are available at Bioinformatics online.


2015 ◽  
Author(s):  
Timothy G Stephens ◽  
Debashish Bhattacharya ◽  
Mark A Ragan ◽  
Cheong Xin Chan

A frequent bottleneck in interpreting phylogenomic output is the need to screen often thousands of trees for features of interest, such as robust clades of specific taxa, as evidence of monophyletic relationship and/or reticulated evolution. Here we present PhySortR, a fast, flexible R package for sorting phylogenetic trees. Unlike existing utilities, PhySortR allows for identification of both exclusive and non-exclusive clades uniting the target taxa, with customisable options to assess clades within the context of the whole tree. PhySortR is a command-line tool that is freely available, highly scalable, and easily automatable.


2019 ◽  
Vol 35 (17) ◽  
pp. 3194-3195 ◽  
Author(s):  
Martin Petr ◽  
Benjamin Vernot ◽  
Janet Kelso

Abstract Summary We present a new R package admixr, which provides a convenient interface for performing reproducible population genetic analyses (f3, D, f4, f4-ratio, qpWave and qpAdm), as implemented by command-line programs in the ADMIXTOOLS software suite. In a traditional ADMIXTOOLS workflow, the user must first generate a set of text configuration files tailored to each individual analysis, often using a combination of shell scripting and manual text editing. The non-tabular output files then need to be parsed to extract values of interest prior to further analyses. Our package simplifies this process by automating all low-level configuration and parsing steps, making analyses as simple as running a single R command. Furthermore, we provide a set of R functions for processing, filtering and manipulating datasets in the EIGENSTRAT format. By unifying all steps of the workflow under a single R framework, this package enables the automation of analytic pipelines, significantly improving the reproducibility of population genetic studies. Availability and implementation The source code of the R package is available under the MIT license. Installation instructions, reference manual and a tutorial can be found on the package website at https://bioinf.eva.mpg.de/admixr. Supplementary information Supplementary data are available at Bioinformatics online.


2020 ◽  
Vol 36 (12) ◽  
pp. 3920-3921
Author(s):  
Mattia Tomasoni ◽  
Sergio Gómez ◽  
Jake Crawford ◽  
Weijia Zhang ◽  
Sarvenaz Choobdar ◽  
...  

Abstract Summary We define a disease module as a partition of a molecular network whose components are jointly associated with one or several diseases or risk factors thereof. Identification of such modules, across different types of networks, has great potential for elucidating disease mechanisms and establishing new powerful biomarkers. To this end, we launched the ‘Disease Module Identification (DMI) DREAM Challenge’, a community effort to build and evaluate unsupervised molecular network modularization algorithms. Here, we present MONET, a toolbox providing easy and unified access to the three top-performing methods from the DMI DREAM Challenge for the bioinformatics community. Availability and implementation MONET is a command line tool for Linux, based on Docker and Singularity containers; the core algorithms were written in R, Python, Ada and C++. It is freely available for download at https://github.com/BergmannLab/MONET.git. Supplementary information Supplementary data are available at Bioinformatics online.


Author(s):  
Lucille Lopez-Delisle ◽  
Leily Rabbani ◽  
Joachim Wolff ◽  
Vivek Bhardwaj ◽  
Rolf Backofen ◽  
...  

Abstract Motivation Generating publication ready plots to display multiple genomic tracks can pose a serious challenge. Making desirable and accurate figures requires considerable effort. This is usually done by hand or by using a vector graphic software. Results pyGenomeTracks (PGT) is a modular plotting tool that easily combines multiple tracks. It enables a reproducible and standardized generation of highly customizable and publication ready images. Availability PGT is available through a graphical interface on https://usegalaxy.eu and through the command line. It is provided on conda via the bioconda channel, on pip and it is openly developed on github: https://github.com/deeptools/pyGenomeTracks. Supplementary information Supplementary data are available at Bioinformatics online.


2018 ◽  
Vol 35 (13) ◽  
pp. 2318-2319 ◽  
Author(s):  
Matthew D Czajkowski ◽  
Daniel P Vance ◽  
Steven A Frese ◽  
Giorgio Casaburi

Abstract Summary The removal of human genomic reads from shotgun metagenomic sequencing is a critical step in protecting subject privacy. Freely available tools addressing this issue require advanced programing knowledge or are limited by analytical time and data load due to their server-based nature. Here, we compared the most cited tools for host-DNA removal using synthetic and real metagenomic datasets. Then, we integrated the most efficient pipeline in a graphical user interface to make these tools available without command line use. This interface, GenCoF, rapidly removes human genome contaminants from metagenomic datasets. Additionally, the tool offers quality-filtering, data reduction and interactive modification of any parameter in order to customize the analysis. GenCoF offers both quality and host-associated filtering in a non-commercial, freely available tool in a local, interactive and easy-to-use interface. Availability and implementation GenCoF is freely available (under a GPL license) for Mac OS and Linux at https://github.com/MattCzajkowski/GenCoF. Supplementary information Supplementary data are available at Bioinformatics online.


2020 ◽  
Vol 36 (15) ◽  
pp. 4366-4368
Author(s):  
Tobias Rohde ◽  
Rita Chupalov ◽  
Nicholas Shulman ◽  
Vagisha Sharma ◽  
Josh Eckels ◽  
...  

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.


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