scholarly journals VCF/Plotein: A web application to facilitate the clinical interpretation of genetic and genomic variants from exome sequencing projects

2018 ◽  
Author(s):  
Raul Ossio ◽  
Diego Said Anaya-Mancilla ◽  
O. Isaac Garcia-Salinas ◽  
Jair S. Garcia-Sotelo ◽  
Luis A. Aguilar ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Web Application ◽  
Medical Community ◽  
Medical Professionals ◽  
Sequencing Data ◽  
Variant Call ◽  
Variant Filtering ◽  
Variant Information ◽  
Or Gene ◽  
User Friendly

ABSTRACTPurposeTo create a user-friendly web application that allows researchers, medical professionals and patients to easily and securely view, filter and interact with human exome sequencing data in the Variant Call Format (VCF).MethodsWe have created VCF/Plotein, a web application written entirely in JavaScript using the Vue.js framework, available at http://vcfplotein.liigh.unam.mx. After a VCF is loaded, gene and variant information is extracted from Ensembl, and cross-referencing with external databases is performed via the Elasticsearch search engine. Support for application-based gene and variant filtering has also been implemented. Interactive graphs are created using the D3.js library. All data processing is done locally in the user’s CPU to ensure the security of patient data.ResultsVCF/Plotein allows users to interactively view and filter VCF files without needing any bioinformatics knowledge. A number of features make it especially suited for the medical community, such as its speed, security, the ability to filter by disease or gene function, and the ease with which information may be shared with collaborators/co-workers.ConclusionVCF/Plotein is a novel web application that allows users to easily and interactively filter and display exome sequencing information, and that is especially suited for bench researchers, medical professionals and patients.

scholarly journals VCF/Plotein: visualization and prioritization of genomic variants from human exome sequencing projects

2019 ◽  
Vol 35 (22) ◽  
pp. 4803-4805 ◽  
Author(s):  
Raul Ossio ◽  
O Isaac Garcia-Salinas ◽  
Diego Said Anaya-Mancilla ◽  
Jair S Garcia-Sotelo ◽  
Luis A Aguilar ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Web Application ◽  
Source Code ◽  
Supplementary Information ◽  
Sequencing Data ◽  
Genomic Variants ◽  
Exome Sequencing Data ◽  
Variant Filtering ◽  
Variant Information ◽  
User Friendly

Abstract Motivation Identifying disease-causing variants from exome sequencing projects remains a challenging task that often requires bioinformatics expertise. Here we describe a user-friendly graphical application that allows medical professionals and bench biologists to prioritize and visualize genetic variants from human exome sequencing data. Results We have implemented VCF/Plotein, a graphical, fully interactive web application able to display exome sequencing data in VCF format. Gene and variant information is extracted from Ensembl. Cross-referencing with external databases and application-based gene and variant filtering have also been implemented. All data processing is done locally by the user’s CPU to ensure the security of patient data. Availability and implementation Freely available on the web at https://vcfplotein.liigh.unam.mx. Website implemented in JavaScript using the Vue.js framework, with all major browsers supported. Source code freely available for download at https://github.com/raulossio/VCF-plotein. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis

2020 ◽  
Author(s):  
Stevenn Volant ◽  
Pierre Lechat ◽  
Perrine Woringer ◽  
Laurence Motreff ◽  
Christophe Malabat ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Data Processing ◽  
Web Application ◽  
Graphical Representation ◽  
Statistical Modelling ◽  
Metagenomic Data ◽  
Sequencing Data ◽  
Microbiome Research ◽  
Interactive Visualizations ◽  
User Friendly

Abstract BackgroundComparing the composition of microbial communities among groups of interest (e.g., patients vs healthy individuals) is a central aspect in microbiome research. It typically involves sequencing, data processing, statistical analysis and graphical representation of the detected signatures. Such an analysis is normally obtained by using a set of different applications that require specific expertise for installation, data processing and in some case, programming skills. ResultsHere, we present SHAMAN, an interactive web application we developed in order to facilitate the use of (i) a bioinformatic workflow for metataxonomic analysis, (ii) a reliable statistical modelling and (iii) to provide among the largest panels of interactive visualizations as compared to the other options that are currently available. SHAMAN is specifically designed for non-expert users who may benefit from using an integrated version of the different analytic steps underlying a proper metagenomic analysis. The application is freely accessible at http://shaman.pasteur.fr/, and may also work as a standalone application with a Docker container (aghozlane/shaman), conda and R. The source code is written in R and is available at https://github.com/aghozlane/shaman. Using two datasets (a mock community sequencing and published 16S rRNA metagenomic data), we illustrate the strengths of SHAMAN in quickly performing a complete metataxonomic analysis. ConclusionsWe aim with SHAMAN to provide the scientific community with a platform that simplifies reproducible quantitative analysis of metagenomic data.

scholarly journals Oasis2.0: improved online analysis of small RNA-seq data

2017 ◽  
Author(s):  
Raza-Ur Rahman ◽  
Abhivyakti Gautam ◽  
Jörn Bethune ◽  
Abdul Sattar ◽  
Maksims Fiosins ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Small Rna ◽  
Small Rnas ◽  
Web Application ◽  
The Novel ◽  
Sequencing Data ◽  
Essential Information ◽  
Deep Sequencing Data ◽  
Small Rna Deep Sequencing ◽  
User Friendly

AbstractOasis 2 is a new main release of the Oasis web application for the detection, differential expression, and classification of small RNAs in deep sequencing data. Compared to its predecessor Oasis, Oasis 2 features a novel and speed-optimized sRNA detection module that supports the identification of small RNAs in any organism with higher accuracy. Next to the improved detection of small RNAs in a target organism, the software now also recognizes potential cross-species miRNAs and viral and bacterial sRNAs in infected samples. In addition, novel miRNAs can now be queried and visualized interactively, providing essential information for over 700 high-quality miRNA predictions across 14 organisms. Robust biomarker signatures can now be obtained using the novel enhanced classification module. Oasis 2 enables biologists and medical researchers to rapidly analyze and query small RNA deep sequencing data with improved precision, recall, and speed, in an interactive and user-friendly environment.Availability and Implementation: Oasis 2 is implemented in Java, J2EE, mysql, Python, R, PHP and JavaScript. It is freely available at http://oasis.dzne.de

scholarly journals re-Searcher: GUI-based bioinformatics tool for simplified genomics data mining of VCF files

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11333
Author(s):  
Daniyar Karabayev ◽  
Askhat Molkenov ◽  
Kaiyrgali Yerulanuly ◽  
Ilyas Kabimoldayev ◽  
Asset Daniyarov ◽  
...  
Keyword(s):  
Web Application ◽  
High Throughput Sequencing ◽  
Sequencing Data ◽  
Data Types ◽  
Standard Format ◽  
Standard Data ◽  
Additional Information ◽  
Link Type ◽  
Sequencing Platforms ◽  
User Friendly

Background High-throughput sequencing platforms generate a massive amount of high-dimensional genomic datasets that are available for analysis. Modern and user-friendly bioinformatics tools for analysis and interpretation of genomics data becomes essential during the analysis of sequencing data. Different standard data types and file formats have been developed to store and analyze sequence and genomics data. Variant Call Format (VCF) is the most widespread genomics file type and standard format containing genomic information and variants of sequenced samples. Results Existing tools for processing VCF files don’t usually have an intuitive graphical interface, but instead have just a command-line interface that may be challenging to use for the broader biomedical community interested in genomics data analysis. re-Searcher solves this problem by pre-processing VCF files by chunks to not load RAM of computer. The tool can be used as standalone user-friendly multiplatform GUI application as well as web application (https://nla-lbsb.nu.edu.kz). The software including source code as well as tested VCF files and additional information are publicly available on the GitHub repository (https://github.com/LabBandSB/re-Searcher).

scholarly journals VarFish - Collaborative and Comprehensive Variant Analysis for Diagnosis and Research

2020 ◽  
Author(s):  
Manuel Holtgrewe ◽  
Oliver Stolpe ◽  
Mikko Nieminen ◽  
Stefan Mundlos ◽  
Alexej Knaus ◽  
...  
Keyword(s):  
Web Application ◽  
Close Collaboration ◽  
Variant Call ◽  
Medical Practitioners ◽  
Genome Browsers ◽  
Collaborative Analysis ◽  
Variant Analysis ◽  
User Friendly ◽  
Multiple Samples ◽  
Variant Assessment

ABSTRACTVarFish is a user-friendly web application for the quality control, filtering, prioritization, analysis, and user-based annotation of panel and exome variant data for rare disease genetics. It is capable of processing variant call files with single or multiple samples. The variants are automatically annotated with population frequencies, molecular impact, and presence in databases such as ClinVar. Further, it provides support for pathogenicity scores including CADD, MutationTaster, and phenotypic similarity scores. Users can filter variants based on these annotations and presumed inheritance pattern and sort the results by these scores. Filtered variants are listed with their annotations and many useful link-outs to genome browsers, other gene/variant data portals, and external tools for variant assessment. VarFish allows user to create their own annotations including support for variant assessment following ACMG-AMP guidelines. In close collaboration with medical practitioners, VarFish was designed for variant analysis and prioritization in diagnostic and research settings as described in the software’s extensive manual. The user interface has been optimized for supporting these protocols. Users can install VarFish on their own in-house servers where it provides additional lab notebook features for collaborative analysis and allows re-analysis of cases, e.g., after update of genotype or phenotype databases.

scholarly journals UTILIZATION OF WHOLE EXOME SEQUENCING DATA TO IDENTIFY CLINICALLY RELEVANT PHARMACOGENOMIC VARIANTS IN INFLAMMATORY BOWEL DISEASE

2021 ◽  
Vol 27 (Supplement_1) ◽  
pp. S32-S32
Author(s):  
Daniel Mulder ◽  
Sam Khalouei ◽  
Neil Warner ◽  
Claudia Gonzaga-Jauregui ◽  
Peter Church ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Clinical Care ◽  
Family Members ◽  
Standard Of Care ◽  
Sequencing Data ◽  
Whole Exome ◽  
Variant Filtering ◽  
Increased Risk ◽  
Whole Exome Sequencing Data

Abstract Objectives We hypothesized that variants within clinically relevant pharmacogenes could be identified using a whole exome sequencing (WES) dataset derived from a cohort of over 1000 IBD patients. Methods Pediatric patients diagnosed with IBD underwent WES. We selected 18 genes with supporting literature where specific exonic variants would influence clinical care. Results We identified actionable pharmacogenes variants in 63% of patients. Importantly, 5% of IBD patients were at risk for serious adverse effects from anaesthesia and 3% were at increased risk for thrombosis. Conclusions We identified exonic variants in the majority of our IBD patients that directly impact clinical care. Flowchart of our pharmacogenomic analysis pipeline. After enrolment (n=2309), each patient underwent whole exome sequencing and sequence alignment. Available family members were also sequenced. Analyzed samples were limited to patients and family members with IBD (n=1097). Pharmacogenes relevant to patients with IBD were identified by literature review and evaluation of pharmGKB (total of 18 genes). Variant filtering was performed using Stargazer and GEMINI frameworks. In our cohort, there were 8 relevant pharmacogenes with variants that would alter clinical care based on current guidelines and standard of care. 63% of the patients had at least one variant that could impact care.

scholarly journals Phrank measures phenotype sets similarity to greatly improve Mendelian diagnostic disease prioritization

2018 ◽  
Author(s):  
Karthik A. Jagadeesh ◽  
Johannes Birgmeier ◽  
Harendra Guturu ◽  
Cole A. Deisseroth ◽  
Aaron M. Wenger ◽  
...  
Keyword(s):  
Information Theory ◽  
Bayesian Network ◽  
Exome Sequencing ◽  
Candidate Genes ◽  
Genetic Diagnosis ◽  
Real Patient ◽  
Variant Filtering ◽  
Busy Clinician ◽  
Or Gene ◽  
Or Genes

AbstractPurposeExome sequencing and diagnosis is beginning to spread across the medical establishment. The most time-consuming part of genome based diagnosis is the manual step of matching the potentially long list of patient candidate genes to patient phenotypes to identify the causative disease.MethodsWe introduce Phrank (for phenotype ranking), an information-theory inspired method that utilizes a Bayesian Network to prioritize candidate diseases or genes, as a stand-alone module that can be run with any underlying knowledgebase and any variant filtering scheme.ResultsPhrank outperforms existing methods at ranking the causative disease or gene when applied to 169 real patient exomes with Mendelian diagnoses. Phrank’s greatest improvement is in disease space, where across all 169 patients it ranks only 3 diseases on average ahead of the true diagnosis, whereas Phenomizer ranks 32 diseases ahead of the causal one.ConclusionUsing Phrank to rank all patient candidate genes or diseases, as they start working through a new case, will save the busy clinician much time in deriving a genetic diagnosis.

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 VarFish: comprehensive DNA variant analysis for diagnostics and research

2020 ◽  
Vol 48 (W1) ◽  
pp. W162-W169 ◽  
Author(s):  
Manuel Holtgrewe ◽  
Oliver Stolpe ◽  
Mikko Nieminen ◽  
Stefan Mundlos ◽  
Alexej Knaus ◽  
...  
Keyword(s):  
Web Application ◽  
Close Collaboration ◽  
Variant Call ◽  
Medical Practitioners ◽  
Genome Browsers ◽  
Collaborative Analysis ◽  
Variant Analysis ◽  
User Friendly ◽  
Multiple Samples ◽  
Variant Assessment

Abstract VarFish is a user-friendly web application for the quality control, filtering, prioritization, analysis, and user-based annotation of DNA variant data with a focus on rare disease genetics. It is capable of processing variant call files with single or multiple samples. The variants are automatically annotated with population frequencies, molecular impact, and presence in databases such as ClinVar. Further, it provides support for pathogenicity scores including CADD, MutationTaster, and phenotypic similarity scores. Users can filter variants based on these annotations and presumed inheritance pattern and sort the results by these scores. Variants passing the filter are listed with their annotations and many useful link-outs to genome browsers, other gene/variant data portals, and external tools for variant assessment. VarFish allows users to create their own annotations including support for variant assessment following ACMG-AMP guidelines. In close collaboration with medical practitioners, VarFish was designed for variant analysis and prioritization in diagnostic and research settings as described in the software's extensive manual. The user interface has been optimized for supporting these protocols. Users can install VarFish on their own in-house servers where it provides additional lab notebook features for collaborative analysis and allows re-analysis of cases, e.g. after update of genotype or phenotype databases.

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