scholarly journals neoANT-HILL: an integrated tool for identification of potential neoantigens

2019 ◽  
Author(s):  
Ana Carolina M F Coelho ◽  
André L Fonseca ◽  
Danilo L Martins ◽  
Lucas M da Cunha ◽  
Paulo B R Lins ◽  
...  
Keyword(s):  
Immune Responses ◽  
False Positive ◽  
Somatic Mutations ◽  
Cancer Genome ◽  
Current Work ◽  
Rna Seq ◽  
Link Type ◽  
Technological Advances ◽  
User Friendly ◽  
Ngs Data

AbstractCancer neoantigens have attracted great interest in immunotherapy due to their ability to elicit antitumoral immune responses. These antigens are formed due to somatic mutations in the cancer genome that result in alterations of the original protein. Although current technological advances in neoantigen identification, it remains a challenging and a large number of false-positive continue to exist. In the current work, we present neoANT-HILL, an automatized user-friendly tool that integrates several immunogenomic analysis to improve neoantigens detection from NGS data. The program input can be a file with somatic mutations called and/or RNA-seq data. Our tool was applied on somatic mutations of melanoma dataset from TCGA and found that neoANT-HILL was able to predicted potential neoantigens. The software is available on github athttps://github.com/neoanthill/neoANT-HILL.

scholarly journals neoANT-HILL: an integrated tool for identification of potential neoantigens

2019 ◽  
Author(s):  
Ana Carolina Coelho ◽  
Sandro de Souza
Keyword(s):  
Immune Cells ◽  
Somatic Mutations ◽  
High Sensitivity ◽  
High Rate ◽  
Graphical Interface ◽  
Rna Seq ◽  
Automated Pipeline ◽  
User Friendly ◽  
Ngs Data ◽  
Multiple Samples

Abstract Background Cancer neoantigens have attracted great interest in immunotherapy due to their capacity to elicit antitumoral responses. These molecules arise from somatic mutations in cancer cells, resulting in alterations on the original protein. Neoantigens identification remains a challenging task due largely to a high rate of false-positives.Results We have developed an efficient and automated pipeline for the identification of potential neoantigens. neoANT-HILL integrates several immunogenomic analyses to improve neoantigen detection from NGS data. The pipeline has been compiled in a pre-built Docker image such that minimal computational background is required for download and setup. NeoANT-HILL was applied in the TCGA melanoma dataset and found several putative neoantigens including ones derived from the recurrent RAC1:P29S and SERPINB3:E250K mutations. neoANT-HILL was also used to identify potential neoantigens in RNA-Seq data with a high sensitivity and specificity.Conclusion neoANT-HILL is a user-friendly tool with a graphical interface that performs neoantigens prediction efficiently. neoANT-HILL is able to process multiple samples, provides several binding predictors, enables quantification of tumor-infiltrating immune cells and considers RNA-Seq data for identifying potential neoantigens. The software is available on Github at https://github.com/neoanthill/neoANT-HILL.

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 ZDOG: zooming in on dominating genes with mutations in cancer pathways

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Rudi Alberts ◽  
Jinyu Chen ◽  
Louxin Zhang
Keyword(s):  
Somatic Mutations ◽  
Positional Information ◽  
Signalling Pathways ◽  
Biological Functions ◽  
Tree Model ◽  
Master Regulators ◽  
Cancer Pathways ◽  
Link Type ◽  
Dominating Tree ◽  
User Friendly

Abstract Background Inference of cancer-causing genes and their biological functions are crucial but challenging due to the heterogeneity of somatic mutations. The heterogeneity of somatic mutations reveals that only a handful of oncogenes mutate frequently and a number of cancer-causing genes mutate rarely. Results We develop a Cytoscape app, named ZDOG, for visualization of the extent to which mutated genes may affect cancer pathways using the dominating tree model. The dominator tree model allows us to examine conveniently the positional importance of a gene in cancer signalling pathways. This tool facilitates the identification of mutated “master” regulators even with low mutation frequency in deregulated signalling pathways. Conclusions We have presented a model for facilitating the examination of the extent to which mutation in a gene may affect downstream components in a signalling pathway through its positional information. The model is implemented in a user-friendly Cytoscape app which will be freely available upon publication. Availability Together with a user manual, the ZDOG app is freely available at GitHub (https://github.com/rudi2013/ZDOG). It is also available in the Cytoscape app store (http://apps.cytoscape.org/apps/ZDOG) and users can easily install it using the Cytoscape App Manager.

scholarly journals MicroScope: ChIP-seq and RNA-seq software analysis suite for gene expression heatmaps

2015 ◽  
Author(s):  
Bohdan B. Khomtchouk ◽  
James R. Hennessy ◽  
Claes Wahlestedt
Keyword(s):  
Web Application ◽  
Differential Expression Analysis ◽  
Dynamic Network ◽  
Principal Component ◽  
Rna Seq ◽  
Software Suite ◽  
Software Analysis ◽  
Link Type ◽  
R Shiny ◽  
User Friendly

AbstractWe propose a user-friendly ChIP-seq and RNA-seq software suite for the interactive visualization and analysis of genomic data, including integrated features to support differential expression analysis, interactive heatmap production, principal component analysis, gene ontology analysis, and dynamic network analysis.MicroScope is hosted online as an R Shiny web application based on the D3 JavaScript library: http://microscopebioinformatics.org/. The methods are implemented in R, and are available as part of the MicroScope project at: https://github.com/Bohdan-Khomtchouk/Microscope.

scholarly journals TACITuS: transcriptomic data collector, integrator, and selector on big data platform

2019 ◽  
Vol 20 (S9) ◽  
Author(s):  
Salvatore Alaimo ◽  
Antonio Di Maria ◽  
Dennis Shasha ◽  
Alfredo Ferro ◽  
Alfredo Pulvirenti
Keyword(s):  
High Throughput ◽  
Rna Seq ◽  
Web Based ◽  
Large Bandwidth ◽  
Specific Analysis ◽  
Galaxy Environment ◽  
Public Repositories ◽  
Microarray Datasets ◽  
User Friendly ◽  
Ngs Data

Abstract Background Several large public repositories of microarray datasets and RNA-seq data are available. Two prominent examples include ArrayExpress and NCBI GEO. Unfortunately, there is no easy way to import and manipulate data from such resources, because the data is stored in large files, requiring large bandwidth to download and special purpose data manipulation tools to extract subsets relevant for the specific analysis. Results TACITuS is a web-based system that supports rapid query access to high-throughput microarray and NGS repositories. The system is equipped with modules capable of managing large files, storing them in a cloud environment and extracting subsets of data in an easy and efficient way. The system also supports the ability to import data into Galaxy for further analysis. Conclusions TACITuS automates most of the pre-processing needed to analyze high-throughput microarray and NGS data from large publicly-available repositories. The system implements several modules to manage large files in an easy and efficient way. Furthermore, it is capable deal with Galaxy environment allowing users to analyze data through a user-friendly interface.

scholarly journals PhageTerm: a Fast and User-friendly Software to Determine Bacteriophage Termini and Packaging Mode using randomly fragmented NGS data

2017 ◽  
Author(s):  
Julian Garneau ◽  
Florence Depardieu ◽  
Louis-Charles Fortier ◽  
David Bikard ◽  
Marc Monot
Keyword(s):  
High Throughput Sequencing ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Link Type ◽  
Sequencing Technologies ◽  
Statistical Framework ◽  
Fastq Format ◽  
Viral Particles ◽  
User Friendly ◽  
Ngs Data

ABSTRACTBacteriophages are the most abundant viruses on earth and display an impressive genetic as well as morphologic diversity. Among those, the most common order of phages is the Caudovirales, whose viral particles packages linear double stranded DNA (dsDNA). In this study we investigated how the information gathered by high throughput sequencing technologies can be used to determine the DNA termini and packaging mechanisms of dsDNA phages. The wet-lab procedures traditionally used for this purpose rely on the identification and cloning of restriction fragment which can be delicate and cumbersome. Here, we developed a theoretical and statistical framework to analyze DNA termini and phage packaging mechanisms using next-generation sequencing data. Our methods, implemented in the PhageTerm software, work with sequencing reads in fastq format and the corresponding assembled phage genome.PhageTerm was validated on a set of phages with well-established packaging mechanisms representative of the termini diversity: 5’cos (lambda), 3’cos (HK97), pac (P1), headful without a pac site (T4), DTR (T7) and host fragment (Mu). In addition, we determined the termini of 9Clostridium difficilephages and 6 phages whose sequences where retrieved from the sequence read archive (SRA).A direct graphical interface is available as a Galaxy wrapper version athttps://galaxy.pasteur.frand a standalone version is accessible athttps://sourceforge.net/projects/phageterm/.

scholarly journals SeqAcademy: an educational pipeline for RNA-Seq and ChIP-Seq analysis

F1000Research ◽  
2020 ◽  
Vol 7 ◽  
pp. 628
Author(s):  
Syed Hussain Ather ◽  
Olaitan Igbagbo Awe ◽  
Thomas J. Butler ◽  
Tamiru Denka ◽  
Stephen Andrew Semick ◽  
...  
Keyword(s):  
Chromatin Immunoprecipitation ◽  
Gene Transcript ◽  
Rna Seq ◽  
Link Type ◽  
Educational Pipeline ◽  
Biological Insight ◽  
Chromatin Immunoprecipitation Sequencing ◽  
Critical Components ◽  
User Friendly

Quantification of gene expression and characterization of gene transcript structures are central problems in molecular biology. RNA sequencing (RNA-Seq) and chromatin immunoprecipitation sequencing (ChIP-Seq) are important methods, but can be cumbersome and difficult for beginners to learn. To teach interested students and scientists how to analyze RNA-Seq and ChIP-Seq data, we present a start-to-finish tutorial for analyzing RNA-Seq and ChIP-Seq data: SeqAcademy (source code: https://github.com/NCBI-Hackathons/seqacademy, webpage: http://www.seqacademy.org/). This user-friendly pipeline, fully written in markdown language, emphasizes the use of publicly available RNA-Seq and ChIP-Seq data and strings together popular tools that bridge that gap between raw sequencing reads and biological insight. We demonstrate practical and conceptual considerations for various RNA-Seq and ChIP-Seq analysis steps with a biological use case - a previously published yeast experiment. This work complements existing sophisticated RNA-Seq and ChIP-Seq pipelines designed for advanced users by gently introducing the critical components of RNA-Seq and ChIP-Seq analysis to the novice bioinformatician. In conclusion, this well-documented pipeline will introduce state-of-the-art RNA-Seq and ChIP-Seq analysis tools to beginning bioinformaticians and help facilitate the analysis of the burgeoning amounts of public RNA-Seq and ChIP-Seq data.

scholarly journals CancerVar: a web server for improved evidence-based clinical interpretation of cancer somatic mutations and copy number abnormalities

2020 ◽  
Author(s):  
Quan Li ◽  
Zilin Ren ◽  
Yunyun Zhou ◽  
Kai Wang
Keyword(s):  
Clinical Significance ◽  
Copy Number ◽  
Somatic Mutations ◽  
Relevant Information ◽  
Web Interface ◽  
Clinical Interpretation ◽  
Link Type ◽  
Command Line Tool ◽  
Hotspot Mutations ◽  
User Friendly

ABSTRACTSeveral knowledgebases, such as CIViC, CGI and OncoKB, have been manually curated to support clinical interpretations of somatic mutations and copy number abnormalities (CNAs) in cancer. However, these resources focus on known hotspot mutations, and discrepancies or even conflicting interpretations have been observed between these knowledgebases. To standardize clinical interpretation, AMP/ASCO/CAP/ACMG/CGC jointly published consensus guidelines for the interpretations of somatic mutations and CNAs in 2017 and 2019, respectively. Based on these guidelines, we developed a standardized, semi-automated interpretation tool called CancerVar (Cancer Variants interpretation), with a user-friendly web interface to assess the clinical impacts of somatic variants. Using a semi-supervised method, CancerVar interpret the clinical impacts of cancer variants as four tiers: strong clinical significance, potential clinical significance, unknown clinical significance, benign/likely benign. CancerVar also allows users to specify criteria or adjust scoring weights as a customized interpretation strategy, and allows phenotype-driven scoring for specific types of cancer. Importantly, CancerVar generates automated texts to summarize clinical evidence on somatic variants, which greatly reduces manual workload to write interpretations that include relevant information from harmonized knowledgebases. CancerVar can be accessed at http://cancervar.wglab.org and it is open to all users without login requirements. The command line tool is also available at https://github.com/WGLab/CancerVar.

scholarly journals neoANT-HILL: an integrated tool for identification of potential neoantigens

2020 ◽  
Author(s):  
Ana Carolina Coelho ◽  
Andre Fonseca ◽  
Danilo Martins ◽  
Paulo Lins ◽  
Lucas da Cunha ◽  
...  
Keyword(s):  
High Sensitivity ◽  
The Cancer Genome Atlas ◽  
High Rate ◽  
Graphical Interface ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
Automated Pipeline ◽  
User Friendly ◽  
Ngs Data ◽  
Multiple Samples

Abstract Background Cancer neoantigens have attracted great interest in immunotherapy due to their capacity to elicit antitumoral responses. These molecules arise from somatic mutations in cancer cells, resulting in alterations on the original protein. Neoantigens identification remains a challenging task due largely to a high rate of false-positives. Results We have developed an efficient and automated pipeline for the identification of potential neoantigens. neoANT-HILL integrates several immunogenomic analyses to improve neoantigen detection from Next Generation Sequence (NGS) data. The pipeline has been compiled in a pre-built Docker image such that minimal computational background is required for download and setup. NeoANT-HILL was applied in the The Cancer Genome Atlas (TCGA) melanoma dataset and found several putative neoantigens including ones derived from the recurrent RAC1:P29S and SERPINB3:E250K mutations. neoANT-HILL was also used to identify potential neoantigens in RNA-Seq data with a high sensitivity and specificity. Conclusion neoANT-HILL is a user-friendly tool with a graphical interface that performs neoantigens prediction efficiently. neoANT-HILL is able to process multiple samples, provides several binding predictors, enables quantification of tumor-infiltrating immune cells and considers RNA-Seq data for identifying potential neoantigens. The software is available on github at https://github.com/neoanthill/neoANT-HILL .

scholarly journals Easymap: A User-Friendly Software Package for Rapid Mapping-by-Sequencing of Point Mutations and Large Insertions

2021 ◽  
Vol 12 ◽  
Author(s):  
Samuel Daniel Lup ◽  
David Wilson-Sánchez ◽  
Sergio Andreu-Sánchez ◽  
José Luis Micol
Keyword(s):  
Point Mutations ◽  
Rapid Identification ◽  
Graphical Interface ◽  
Rna Seq ◽  
Source Program ◽  
Next Generation Sequencing Ngs ◽  
User Friendly ◽  
Ngs Data ◽  
Mapping By Sequencing ◽  
Generation Sequencing

Mapping-by-sequencing strategies combine next-generation sequencing (NGS) with classical linkage analysis, allowing rapid identification of the causal mutations of the phenotypes exhibited by mutants isolated in a genetic screen. Computer programs that analyze NGS data obtained from a mapping population of individuals derived from a mutant of interest to identify a causal mutation are available; however, the installation and usage of such programs requires bioinformatic skills, modifying or combining pieces of existing software, or purchasing licenses. To ease this process, we developed Easymap, an open-source program that simplifies the data analysis workflows from raw NGS reads to candidate mutations. Easymap can perform bulked segregant mapping of point mutations induced by ethyl methanesulfonate (EMS) with DNA-seq or RNA-seq datasets, as well as tagged-sequence mapping for large insertions, such as transposons or T-DNAs. The mapping analyses implemented in Easymap have been validated with experimental and simulated datasets from different plant and animal model species. Easymap was designed to be accessible to all users regardless of their bioinformatics skills by implementing a user-friendly graphical interface, a simple universal installation script, and detailed mapping reports, including informative images and complementary data for assessment of the mapping results. Easymap is available at http://genetics.edu.umh.es/resources/easymap; its Quickstart Installation Guide details the recommended procedure for installation.

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