scholarly journals PathScore: a web tool for identifying altered pathways in cancer data

2016 ◽  
Author(s):  
Stephen G. Gaffney ◽  
Jeffrey P. Townsend
Keyword(s):  
Web Application ◽  
Somatic Mutations ◽  
Supplementary Information ◽  
Web Tool ◽  
Cancer Data ◽  
Link Type ◽  
Novel Approach ◽  
Supplementary Material ◽  
User Friendly ◽  
Pathway Effect

ABSTRACTSummaryPathScore quantifies the level of enrichment of somatic mutations within curated pathways, applying a novel approach that identifies pathways enriched across patients. The application provides several user-friendly, interactive graphic interfaces for data exploration, including tools for comparing pathway effect sizes, significance, gene-set overlap and enrichment differences between projects.Availability and ImplementationWeb application available at pathscore.publichealth.yale.edu. Site implemented in Python and MySQL, with all major browsers supported. Source code available at github.com/sggaffney/pathscore with a GPLv3 [email protected] InformationAdditional documentation can be found at http://pathscore.publichealth.yale.edu/faq.

scholarly journals G4Killer web application: a tool to design G-quadruplex mutations

2020 ◽  
Vol 36 (10) ◽  
pp. 3246-3247
Author(s):  
Vaclav Brazda ◽  
Jan Kolomaznik ◽  
Jean-Louis Mergny ◽  
Jiri Stastny
Keyword(s):  
Dna Sequences ◽  
Web Application ◽  
Rational Design ◽  
Therapeutic Potential ◽  
Supplementary Information ◽  
Web Tool ◽  
Web Based ◽  
Dna Structures ◽  
G Quadruplex ◽  
User Friendly

Abstract Motivation G-quadruplexes (G4) are important regulatory non-B DNA structures with therapeutic potential. A tool for rational design of mutations leading to decreased propensity for G4 formation should be useful in studying G4 functions. Although tools exist for G4 prediction, no easily accessible tool for the rational design of G4 mutations has been available. Results We developed a web-based tool termed G4Killer that is based on the G4Hunter algorithm. This new tool is a platform-independent and user-friendly application to design mutations crippling G4 propensity in a parsimonious way (i.e., keeping the primary sequence as close as possible to the original one). The tool is integrated into our DNA analyzer server and allows for generating mutated DNA sequences having the desired lowered G4Hunter score with minimal mutation steps. Availability and implementation The G4Killer web tool can be accessed at: http://bioinformatics.ibp.cz. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals MeltingPlot: a user-friendly online tool for epidemiological investigation using High Resolution Melting data

2020 ◽  
Author(s):  
Matteo Perini ◽  
Gherard Batisti Biffignandi ◽  
Domenico Di Carlo ◽  
Ajay Ratan Pasala ◽  
Aurora Piazza ◽  
...  
Keyword(s):  
High Resolution ◽  
High Resolution Melting ◽  
Epidemiological Studies ◽  
Supplementary Information ◽  
Web Interface ◽  
Web Tool ◽  
Online Tool ◽  
Link Type ◽  
Surveillance Programs ◽  
User Friendly

AbstractSummaryMeltingPlot is an open source web tool for pathogen typing and epidemiological investigations using High Resolution Melting (HRM) data. The tool implements a graph-based algorithm designed to discriminate pathogen clones on the basis of HRM data, producing portable typing results. MeltingPlot also merges typing information with isolates and patients metadata to create graphical and tabular outputs useful in epidemiological studies. HRM technique allows pathogen typing in less than 5 hours with ~5 euros per sample. MeltingPlot is the first tool specifically designed for HRM-based epidemiological studies and it can analyse hundreds of isolates in a few seconds. Thus, the use of MeltingPlot makes HRM-based typing suitable for large surveillance programs as well as for rapid outbreak reconstructions.Availability and implementationMeltingPlot is implemented in R.The web interface is available at https://skynet.unimi.it/index.php/tools/meltingplot.The source code is also available at https://github.com/MatteoPS/[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/

scholarly journals GenomeScope: Fast reference-free genome profiling from short reads

2016 ◽  
Author(s):  
Gregory W. Vurture ◽  
Fritz J. Sedlazeck ◽  
Maria Nattestad ◽  
Charles J. Underwood ◽  
Han Fang ◽  
...  
Keyword(s):  
Error Rates ◽  
Supplementary Information ◽  
Web Tool ◽  
Short Reads ◽  
Link Type ◽  
Repeat Content ◽  
A Genome ◽  
Wide Range ◽  
Supplementary Material ◽  
Downstream Analysis

AbstractSummaryGenomeScope is an open-source web tool to rapidly estimate the overall characteristics of a genome, including genome size, heterozygosity rate, and repeat content from unprocessed short reads. These features are essential for studying genome evolution, and help to choose parameters for downstream analysis. We demonstrate its accuracy on 324 simulated and 16 real datasets with a wide range in genome sizes, heterozygosity levels, and error rates.Availability and Implementationhttp://genomescope.org, https://github.com/schatzlab/[email protected] informationSupplementary data are available at Bioinformatics online.

scholarly journals mirtronDB: a mirtron knowledge base

2018 ◽  
Author(s):  
Bruno Henrique Ribeiro Da Fonseca ◽  
Douglas Silva Domingues ◽  
Alexandre Rossi Paschoal
Keyword(s):  
Knowledge Base ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Knowledge Database ◽  
Group Type ◽  
Link Type ◽  
Supplementary Material ◽  
Access To Knowledge ◽  
User Friendly ◽  
Organism Group

AbstractMotivationMirtrons are originated from short introns with atypical cleavage from the miRNA canonical pathway by using the splicing mechanism. Several studies describe mirtrons in chordates, invertebrates and plants but in the current literature there is no repository that centralizes and organizes these public and available data. To fill this gap, we created the first knowledge database dedicated to mirtron, called mirtronDB, available at http://mirtrondb.cp.utfpr.edu.br/. MirtronDB has a total of 1,407 mirtron precursors and 2,426 mirtron mature sequences in 18 species.ResultsThrough a user-friendly interface, users can browse and search mirtrons by organism, organism group, type and name. MirtronDB is a specialized resource to explore mirtrons and their regulations, providing free, user-friendly access to knowledge on mirtron data.AvailabilityMirtronDB is available at http://mirtrondb.cp.utfpr.edu.br/[email protected] informationSupplementary data are available.

scholarly journals Biopipe: A Lightweight System Enabling Comparison of Bioinformatics Tools and Workflows

2017 ◽  
Author(s):  
Saima Sultana Tithi ◽  
Jiyoung Lee ◽  
Liqing Zhang ◽  
Song Li ◽  
Na Meng
Keyword(s):  
Web Application ◽  
Supplementary Information ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Web Interfaces ◽  
Link Type ◽  
Bioinformatics Tools ◽  
Multiple Alternative ◽  
Portable System ◽  
User Friendly

AbstractAnalyzing next generation sequencing data always requires researchers to install many tools, prepare input data compliant to the required data format, and execute the tools in specific orders. Such tool installation and workflow execution process is tedious and error-prone, and becomes very challenging when researchers need to compare multiple alternative tool chains. To mitigate this problem, we developed a new lightweight and portable system, Biopipe, to simplify the creation and execution of bioinformatics tools and workflows, and to further enable the comparison between alternative tools or workflows. Biopipe allows users to create and edit workflows with user-friendly web interfaces, and automates tool installation as well as workflow synthesis by downloading and executing predefined Docker images. With Biopipe, biologists can easily experiment with and compare different bioinformatics tools and workflows without much computer science knowledge. There are mainly two parts in Biopipe: a web application and a standalone Java application. They are freely available at http://bench.cs.vt.edu:8282/Biopipe-Workflow-Editor-0.0.1/index.xhtml and https://code.vt.edu/saima5/[email protected] informationSupplementary data are available online.

scholarly journals The winning methods for predicting cellular position in the DREAM single cell transcriptomics challenge

2020 ◽  
Author(s):  
Vu VH Pham ◽  
Xiaomei Li ◽  
Buu Truong ◽  
Thin Nguyen ◽  
Lin Liu ◽  
...  
Keyword(s):  
Single Cell ◽  
Web Application ◽  
Single Cells ◽  
Drosophila Embryo ◽  
Supplementary Information ◽  
Rna Seq ◽  
Link Type ◽  
Spatial Reconstruction ◽  
Spatial Environment ◽  
Supplementary Material

AbstractMotivationPredicting cell locations is important since with the understanding of cell locations, we may estimate the function of cells and their integration with the spatial environment. Thus, the DREAM Challenge on Single Cell Transcriptomics required participants to predict the locations of single cells in the Drosophila embryo using single cell transcriptomic data.ResultsWe have developed over 50 pipelines by combining different ways of pre-processing the RNA-seq data, selecting the genes, predicting the cell locations, and validating predicted cell locations, resulting in the winning methods for two out of three sub-challenges in the competition. In this paper, we present an R package, SCTCwhatateam, which includes all the methods we developed and the Shiny web-application to facilitate the research on single cell spatial reconstruction. All the data and the example use cases are available in the Supplementary material.AvailabilityThe scripts of the package are available at https://github.com/thanhbuu04/SCTCwhatateam and the Shiny application is available at https://github.com/pvvhoang/[email protected] informationSupplementary data are available at Briefings in Bioinformatics online.

scholarly journals COVID-Align: Accurate online alignment of hCoV-19 genomes using a profile HMM

2020 ◽  
Author(s):  
Frédéric Lemoine ◽  
Luc Blassel ◽  
Jakub Voznica ◽  
Olivier Gascuel
Keyword(s):  
Daily Basis ◽  
Supplementary Information ◽  
Summary Statistics ◽  
Evolutionary Novelty ◽  
Bioinformatics Analyses ◽  
Link Type ◽  
Sequencing Quality ◽  
User Friendly ◽  
Profile Hmm ◽  
New Mutations

AbstractMotivationThe first cases of the COVID-19 pandemic emerged in December 2019. Until the end of February 2020, the number of available genomes was below 1,000, and their multiple alignment was easily achieved using standard approaches. Subsequently, the availability of genomes has grown dramatically. Moreover, some genomes are of low quality with sequencing/assembly errors, making accurate re-alignment of all genomes nearly impossible on a daily basis. A more efficient, yet accurate approach was clearly required to pursue all subsequent bioinformatics analyses of this crucial data.ResultshCoV-19 genomes are highly conserved, with very few indels and no recombination. This makes the profile HMM approach particularly well suited to align new genomes, add them to an existing alignment and filter problematic ones. Using a core of ∼2,500 high quality genomes, we estimated a profile using HMMER, and implemented this profile in COVID-Align, a user-friendly interface to be used online or as standalone via Docker. The alignment of 1,000 genomes requires less than 20mn on our cluster. Moreover, COVID-Align provides summary statistics, which can be used to determine the sequencing quality and evolutionary novelty of input genomes (e.g. number of new mutations and indels).Availabilityhttps://covalign.pasteur.cloud, hub.docker.com/r/evolbioinfo/[email protected], [email protected] informationSupplementary information is available at Bioinformatics online.

Palaeolatitudinal distribution of the Ediacaran macrobiota

2021 ◽  
pp. jgs2021-030
Author(s):  
Catherine E. Boddy ◽  
Emily G. Mitchell ◽  
Andrew Merdith ◽  
Alexander G. Liu
Keyword(s):  
Taxonomic Composition ◽  
Supplementary Information ◽  
Cambrian Explosion ◽  
Content Type ◽  
Link Type ◽  
Environmental Perturbations ◽  
Significant Difference ◽  
Evolutionary Trajectories ◽  
Cambrian Radiation ◽  
Supplementary Material

Macrofossils of the late Ediacaran Period (c. 579–539 Ma) document diverse, complex multicellular eukaryotes, including early animals, prior to the Cambrian radiation of metazoan phyla. To investigate the relationships between environmental perturbations, biotic responses and early metazoan evolutionary trajectories, it is vital to distinguish between evolutionary and ecological controls on the global distribution of Ediacaran macrofossils. The contributions of temporal, palaeoenvironmental and lithological factors in shaping the observed variations in assemblage taxonomic composition between Ediacaran macrofossil sites are widely discussed, but the role of palaeogeography remains ambiguous. Here we investigate the influence of palaeolatitude on the spatial distribution of Ediacaran macrobiota through the late Ediacaran Period using two leading palaeogeographical reconstructions. We find that overall generic diversity was distributed across all palaeolatitudes. Among specific groups, the distributions of candidate ‘Bilateral’ and Frondomorph taxa exhibit weakly statistically significant and statistically significant differences between low and high palaeolatitudes within our favoured palaeogeographical reconstruction, respectively, whereas Algal, Tubular, Soft-bodied and Biomineralizing taxa show no significant difference. The recognition of statistically significant palaeolatitudinal differences in the distribution of certain morphogroups highlights the importance of considering palaeolatitudinal influences when interrogating trends in Ediacaran taxon distributions.Supplementary material: Supplementary information, data and code are available at https://doi.org/10.6084/m9.figshare.c.5488945Thematic collection: This article is part of the Advances in the Cambrian Explosion collection available at: https://www.lyellcollection.org/cc/advances-cambrian-explosion

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.

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