scholarly journals PrimerServer: a high-throughput primer design and specificity-checking platform

2017 ◽  
Author(s):  
Tao Zhu ◽  
Chengzhen Liang ◽  
Zhigang Meng ◽  
Yanyan Li ◽  
Yayu Wu ◽  
...  
Keyword(s):  
High Throughput ◽  
Molecular Breeding ◽  
Primer Design ◽  
Command Line ◽  
Specific Primers ◽  
Data Presentation ◽  
Medical Testing ◽  
Link Type ◽  
Fast Running

AbstractSummaryDesigning specific primers for multiple sites across the whole genome is still challenging, especially in species with complex genomes. Here we present PrimerServer, a high-throughput primer design and specificity-checking platform with both web and command-line interfaces. This platform efficiently integrates site selection, primer design, specificity checking and data presentation. In our case study, PrimerServer achieved high accuracy and a fast running speed for a large number of sites, suggesting its potential for molecular biology applications such as molecular breeding or medical testing.Availability and ImplementationSource code for PrimerServer is available at https://github.com/billzt/PrimerServer. A demo server is freely accessible at https://primerserver.org, with all major browsers [email protected] or [email protected]

scholarly journals BioKEEN: A library for learning and evaluating biological knowledge graph embeddings

2018 ◽  
Author(s):  
Mehdi Ali ◽  
Charles Tapley Hoyt ◽  
Daniel Domingo-Fernández ◽  
Jens Lehmann ◽  
Hajira Jabeen
Keyword(s):  
Knowledge Graph ◽  
Biological Knowledge ◽  
Command Line ◽  
Graph Embeddings ◽  
Command Line Interface ◽  
Software Ecosystem ◽  
Link Type ◽  
Mapping Resource ◽  
Significant Attention

AbstractKnowledge graph embeddings (KGEs) have received significant attention in other domains due to their ability to predict links and create dense representations for graphs’ nodes and edges. However, the software ecosystem for their application to bioinformatics remains limited and inaccessible for users without expertise in programming and machine learning. Therefore, we developed BioKEEN (Biological KnowlEdge EmbeddiNgs) and PyKEEN (Python KnowlEdge EmbeddiNgs) to facilitate their easy use through an interactive command line interface. Finally, we present a case study in which we used a novel biological pathway mapping resource to predict links that represent pathway crosstalks and hierarchies.AvailabilityBioKEEN and PyKEEN are open source Python packages publicly available under the MIT License at https://github.com/SmartDataAnalytics/BioKEEN and https://github.com/SmartDataAnalytics/PyKEEN as well as through PyPI.

scholarly journals Phigaro: high throughput prophage sequence annotation

2019 ◽  
Author(s):  
Elizaveta V. Starikova ◽  
Polina O. Tikhonova ◽  
Nikita A. Prianichnikov ◽  
Chris M. Rands ◽  
Evgeny M. Zdobnov ◽  
...  
Keyword(s):  
Test Data ◽  
High Throughput ◽  
Source Code ◽  
Sequence Annotation ◽  
Command Line ◽  
Link Type ◽  
Genome Maps ◽  
Transposon Insertion ◽  
Prophage Sequence

AbstractSummaryPhigaro is a standalone command-line application that is able to detect prophage regions taking raw genome and metagenome assemblies as an input. It also produces dynamic annotated “prophage genome maps” and marks possible transposon insertion spots inside prophages. It provides putative taxonomic annotations that can distinguish tailed from non-tailed phages. It is applicable for mining prophage regions from large metagenomic datasets.AvailabilitySource code for Phigaro is freely available for download at https://github.com/bobeobibo/phigaro along with test data. The code is written in Python.

scholarly journals SpeciesPrimer: a bioinformatics pipeline dedicated to the design of qPCR primers for the quantification of bacterial species

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8544
Author(s):  
Matthias Dreier ◽  
Hélène Berthoud ◽  
Noam Shani ◽  
Daniel Wechsler ◽  
Pilar Junier
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Bacterial Species ◽  
Primer Design ◽  
Diagnostic Methods ◽  
Food Microbiology ◽  
Fermented Foods ◽  
Bioinformatics Pipeline ◽  
Specific Primers ◽  
Species Specific

Background Quantitative real-time PCR (qPCR) is a well-established method for detecting and quantifying bacteria, and it is progressively replacing culture-based diagnostic methods in food microbiology. High-throughput qPCR using microfluidics brings further advantages by providing faster results, decreasing the costs per sample and reducing errors due to automatic distribution of samples and reagents. In order to develop a high-throughput qPCR approach for the rapid and cost-efficient quantification of microbial species in complex systems such as fermented foods (for instance, cheese), the preliminary setup of qPCR assays working efficiently under identical PCR conditions is required. Identification of target-specific nucleotide sequences and design of specific primers are the most challenging steps in this process. To date, most available tools for primer design require either laborious manual manipulation or high-performance computing systems. Results We developed the SpeciesPrimer pipeline for automated high-throughput screening of species-specific target regions and the design of dedicated primers. Using SpeciesPrimer, specific primers were designed for four bacterial species of importance in cheese quality control, namely Enterococcus faecium, Enterococcus faecalis, Pediococcus acidilactici and Pediococcus pentosaceus. Selected primers were first evaluated in silico and subsequently in vitro using DNA from pure cultures of a variety of strains found in dairy products. Specific qPCR assays were developed and validated, satisfying the criteria of inclusivity, exclusivity and amplification efficiencies. Conclusion In this work, we present the SpeciesPrimer pipeline, a tool to design species-specific primers for the detection and quantification of bacterial species. We use SpeciesPrimer to design qPCR assays for four bacterial species and describe a workflow to evaluate the designed primers. SpeciesPrimer facilitates efficient primer design for species-specific quantification, paving the way for a fast and accurate quantitative investigation of microbial communities.

scholarly journals fluff: exploratory analysis and visualization of high-throughput sequencing data

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2209 ◽  
Author(s):  
Georgios Georgiou ◽  
Simon J. van Heeringen
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Developmental Stages ◽  
Command Line ◽  
Clustering Methods ◽  
Sequencing Data ◽  
Link Type ◽  
High Throughput Sequencing Data ◽  
Genome Wide ◽  
Genome Wide Data

Summary.In this article we describe fluff, a software package that allows for simple exploration, clustering and visualization of high-throughput sequencing data mapped to a reference genome. The package contains three command-line tools to generate publication-quality figures in an uncomplicated manner using sensible defaults. Genome-wide data can be aggregated, clustered and visualized in a heatmap, according to different clustering methods. This includes a predefined setting to identify dynamic clusters between different conditions or developmental stages. Alternatively, clustered data can be visualized in a bandplot. Finally, fluff includes a tool to generate genomic profiles. As command-line tools, the fluff programs can easily be integrated into standard analysis pipelines. The installation is straightforward and documentation is available athttp://fluff.readthedocs.org.Availability.fluff is implemented in Python and runs on Linux. The source code is freely available for download athttps://github.com/simonvh/fluff.

scholarly journals AmpliconDesign – An interactive web server for the design of high-throughput targeted DNA methylation assays

2020 ◽  
Author(s):  
Maximilian Schönung ◽  
Jana Hess ◽  
Pascal Bawidamann ◽  
Sina Stäble ◽  
Joschka Hey ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Quality Control ◽  
High Throughput ◽  
Dna Sequences ◽  
Web Server ◽  
Dna Amplification ◽  
Pcr Primers ◽  
Primer Design ◽  
Link Type ◽  
Targeted Analysis

ABSTRACTTargeted analysis of DNA methylation patterns based on bisulfite-treated genomic DNA (BT-DNA) is considered as a gold-standard for epigenetic biomarker development. Existing software tools facilitate primer design, primer quality control or visualization of primer localization. However, high-throughput design of primers for BT-DNA amplification is hampered by limits in throughput and functionality of existing tools, requiring users to repeatedly perform specific tasks manually. Consequently, the design of PCR primers for BT-DNA remains a tedious and time-consuming process. To bridge this gap, we developed AmpliconDesign, a webserver providing a scalable and user-friendly platform for the design and analysis of targeted DNA methylation studies based on BT-DNA, e.g. deep amplicon bisulfite sequencing (ampBS-seq), EpiTYPER MassArray, or pyrosequencing. Core functionality of the web server includes high-throughput primer design and binding site validation based on in silico bisulfite-converted DNA sequences, prediction of fragmentation patterns for EpiTYPER MassArray, an interactive quality control as well as a streamlined analysis workflow for ampBS-seq.Availability and ImplementationThe AmpliconDesign webserver is freely available online at: https://amplicondesign.dkfz.de/. AmpliconDesign has been implemented using the R Shiny framework (Chang et al., 2018). The source code is publicly available under the GNU General Public License v3.0 (https://github.com/MaxSchoenung/AmpliconDesign).ContactDaniel B. Lipka ([email protected]) & Maximilian Schönung ([email protected])

scholarly journals AGEpy: a Python package for computational biology

2018 ◽  
Author(s):  
Franziska Metge ◽  
Robert Sehlke ◽  
Jorge Boucas
Keyword(s):  
Computational Biology ◽  
Open Source ◽  
High Throughput ◽  
Biological Data ◽  
Command Line ◽  
High Throughput Analysis ◽  
Throughput Analysis ◽  
Link Type ◽  
Biological Meaning ◽  
Python Package

AbstractSummary:AGEpy is a Python package focused on the transformation of interpretable data into biological meaning. It is designed to support high-throughput analysis of pre-processed biological data using either local Python based processing or Python based API calls to local or remote servers. In this application note we describe its different Python modules as well as its command line accessible toolsaDiff,abed,blasto,david, andobo2tsv.Availability:The open source AGEpy Python package is freely available at:https://github.com/mpg-age-bioinformatics/AGEpy.Contact:[email protected]

scholarly journals Bar-seq strategies for the LeishGEdit toolbox

2020 ◽  
Author(s):  
Tom Beneke ◽  
Eva Gluenz
Keyword(s):  
High Throughput ◽  
Gene Function ◽  
Gene Editing ◽  
Primer Design ◽  
List Type ◽  
Loss Of Function ◽  
Link Type ◽  
Analysis Tools ◽  
Mixed Populations

AbstractThe number of fully sequenced genomes increases steadily but the function of many genes remains unstudied. To accelerate dissection of gene function in Leishmania spp. and other kinetoplastids we developed previously a streamlined pipeline for CRISPR-Cas9 gene editing, which we termed LeishGEdit [1]. To facilitate high-throughput mutant screens we have adapted this pipeline by barcoding mutants with unique 17-nucleotide barcodes, allowing loss-of-function screens in mixed populations [2]. Here we present primer design and analysis tools that facilitate these bar-seq strategies. We have developed a standalone easy-to-use pipeline to design CRISPR primers suitable for the LeishGEdit toolbox for any given genome and have generated a list of 14,995 barcodes. Barcodes and oligos are now accessible through our website www.leishgedit.net allowing to pursue bar-seq experiments in all currently available TriTrypDB genomes (release 41). This will streamline CRISPR bar-seq assays in kinetoplastids, enabling pooled mutant screens across the community.HighlightsDeveloping tools for pooled bar-seq mutant screens across the kinetoplastid communityDevelopment of a standalone script to design primers suitable for the LeishGEdit toolboxGeneration of 14,995 barcodes that can be used for bar-seq strategies in kinetoplastidsBar-seq primers for all TriTrypDB genomes (release 41) can be obtained from www.leishgedit.net

scholarly journals SpeciesPrimer: A bioinformatics pipeline dedicated to the design of qPCR primers for the quantification of bacterial species

2019 ◽  
Author(s):  
Matthias Dreier ◽  
Hélène Berthoud ◽  
Noam Shani ◽  
Daniel Wechsler ◽  
Pilar Junier
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Bacterial Species ◽  
Primer Design ◽  
Diagnostic Methods ◽  
Food Microbiology ◽  
Bioinformatics Pipeline ◽  
Specific Primers ◽  
Species Specific

Background. Quantitative real-time PCR (qPCR) is a well-established method for detecting and quantifying bacteria, and it is progressively replacing culture-based diagnostic methods in food microbiology. High-throughput qPCR using microfluidics brings further advantages by providing faster results, decreasing the costs per sample and reducing errors due to automatic distribution of samples and reactants. In order to develop a high-throughput qPCR approach for the rapid and cost-efficient quantification of microbial species in a given system (for instance, cheese), the preliminary setup of qPCR assays working efficiently under identical PCR conditions is required. Identification of target-specific nucleotide sequences and design of specific primers are the most challenging steps in this process. To date, most available tools for primer design require either laborious manual manipulation or high-performance computing systems. Results. We developed the SpeciesPrimer pipeline for automated high-throughput screening of species-specific target regions and the design of dedicated primers. Using SpeciesPrimer specific primers were designed for four bacterial species of importance in cheese quality control, namely Enterococcus faecium, Enterococcus faecalis, Pediococcus acidilactici and Pediococcus pentosaceus. Selected primers were first evaluated in silico and subsequently in vitro using DNA from pure cultures of a variety of strains found in dairy products. Specific qPCR assays were developed and validated, satisfying the criteria of inclusivity, exclusivity and amplification efficiencies. Conclusion. In this work, we present the SpeciesPrimer pipeline, a tool to design species-specific primers for the detection and quantification of bacterial species. We use SpeciesPrimer to design qPCR assays for four bacterial species and describe a workflow to evaluate the designed primers. SpeciesPrimer facilitates efficient primer design for species-specific quantification, paving the way for a fast and accurate quantitative investigation of microbial communities.

scholarly journals SpeciesPrimer: A bioinformatics pipeline dedicated to the design of qPCR primers for the quantification of bacterial species

2019 ◽  
Author(s):  
Matthias Dreier ◽  
Hélène Berthoud ◽  
Noam Shani ◽  
Daniel Wechsler ◽  
Pilar Junier
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Bacterial Species ◽  
Primer Design ◽  
Diagnostic Methods ◽  
Food Microbiology ◽  
Bioinformatics Pipeline ◽  
Specific Primers ◽  
Species Specific

Background. Quantitative real-time PCR (qPCR) is a well-established method for detecting and quantifying bacteria, and it is progressively replacing culture-based diagnostic methods in food microbiology. High-throughput qPCR using microfluidics brings further advantages by providing faster results, decreasing the costs per sample and reducing errors due to automatic distribution of samples and reactants. In order to develop a high-throughput qPCR approach for the rapid and cost-efficient quantification of microbial species in a given system (for instance, cheese), the preliminary setup of qPCR assays working efficiently under identical PCR conditions is required. Identification of target-specific nucleotide sequences and design of specific primers are the most challenging steps in this process. To date, most available tools for primer design require either laborious manual manipulation or high-performance computing systems. Results. We developed the SpeciesPrimer pipeline for automated high-throughput screening of species-specific target regions and the design of dedicated primers. Using SpeciesPrimer specific primers were designed for four bacterial species of importance in cheese quality control, namely Enterococcus faecium, Enterococcus faecalis, Pediococcus acidilactici and Pediococcus pentosaceus. Selected primers were first evaluated in silico and subsequently in vitro using DNA from pure cultures of a variety of strains found in dairy products. Specific qPCR assays were developed and validated, satisfying the criteria of inclusivity, exclusivity and amplification efficiencies. Conclusion. In this work, we present the SpeciesPrimer pipeline, a tool to design species-specific primers for the detection and quantification of bacterial species. We use SpeciesPrimer to design qPCR assays for four bacterial species and describe a workflow to evaluate the designed primers. SpeciesPrimer facilitates efficient primer design for species-specific quantification, paving the way for a fast and accurate quantitative investigation of microbial communities.

scholarly journals fluff: exploratory analysis and visualization of high-throughput sequencing data

2016 ◽  
Author(s):  
Georgios Georgiou ◽  
Simon J. van Heeringen
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Developmental Stages ◽  
Command Line ◽  
Clustering Methods ◽  
Sequencing Data ◽  
Link Type ◽  
High Throughput Sequencing Data ◽  
Genome Wide ◽  
Genome Wide Data

AbstractSummaryIn this application note we describe fluff, a software package that allows for simple exploration, clustering and visualization of high-throughput sequencing data mapped to a reference genome. The package contains three command-line tools to generate publication-quality figures in an uncomplicated manner using sensible defaults. Genome-wide data can be aggregated, clustered and visualized in a heatmap, according to different clustering methods. This includes a predefined setting to identify dynamic clusters between different conditions or developmental stages. Alternatively, clustered data can be visualized in a bandplot. Finally, fluff includes a tool to generate genomic profiles. As command-line tools, the fluff programs can easily be integrated into standard analysis pipelines. The installation is straightforward and documentation is available at http://fluff.readthedocs.org.Availabilityfluff is implemented in Python and runs on Linux. The source code is freely available for download at http://github.com/simonvh/[email protected]

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