scholarly journals miRGalaxy: Galaxy-Based Framework for Interactive Analysis of microRNA and isomiR Sequencing Data

Cancers ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 5663
Author(s):  
Ilias Glogovitis ◽  
Galina Yahubyan ◽  
Thomas Würdinger ◽  
Danijela Koppers-Lalic ◽  
Vesselin Baev
Keyword(s):  
Small Rna ◽  
Data Analytics ◽  
Comprehensive Analysis ◽  
Sequencing Data ◽  
Detailed Structure ◽  
Diagnostic Biomarkers ◽  
Interactive Analysis ◽  
Depth Analysis ◽  
Structure Complexity ◽  
User Friendly

Tools for microRNA (miR) sequencing data analyses are broadly used in biomedical research. However, the complexity of computational approaches still remains a challenge for biologists with scarce experience in data analytics and bioinformatics. Here, we present miRGalaxy, a Galaxy-based framework for comprehensive analysis of miRs and their sequence variants—miR isoforms (isomiRs). Though isomiRs are commonly reported in deep-sequencing experiments, their detailed structure complexity and specific differential expression (DE) remain not fully examined by the majority of the available analysis tools. miRGalaxy encompasses biologist-user-friendly tools and workflows dedicated to the analysis of the isomiR-ome and its complex behavior in various biological samples. miRGalaxy is developed as a modular, accessible, redistributable, shareable, and user-friendly framework for scientists working with small RNA (sRNA)-seq data. Due to its modular workflow, advanced users can customize the steps and tools for their needs. In addition, the framework provides an analysis report where the significant output results are summarized in charts and visualizations. miRGalaxy can be accessed via preconfigured Docker image flavor and a Toolshed installation if the user already has a running Galaxy instance. Over the last decade, studies on the expression of miRs and isomiRs in normal and deregulated tissues have led to the discovery of their potential as diagnostic biomarkers. The detection of miRs in biofluids further expanded the exploration of the miR repertoire as a source of liquid biopsy biomarkers. Here we show the miRGalaxy framework application for in-depth analysis of the sRNA-seq data from two different biofluids, milk and plasma, to identify, annotate, and discover specific differentially expressed miRs and isomiRs.

scholarly journals DBtRend: A Web-Server of tRNA Expression Profiles from Small RNA Sequencing Data in Humans

Genes ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1576
Author(s):  
Jin-Ok Lee ◽  
Minho Lee ◽  
Yeun-Jun Chung
Keyword(s):  
Small Rna ◽  
Molecular Subtype ◽  
Expression Profiles ◽  
Web Server ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
Microrna Sequencing ◽  
User Friendly

Transfer RNA (tRNA), a key component of the translation machinery, plays critical roles in stress conditions and various diseases. While knowledge regarding the importance of tRNA function is increasing, its biological roles are still not well understood. There is currently no comprehensive database or web server providing the expression landscape of tRNAs across a variety of human tissues and diseases. Here, we constructed a user-friendly and interactive database, DBtRend, which provides a profile of mature tRNA expression across various biological conditions by reanalyzing the small RNA or microRNA sequencing data from the Cancer Genome Atlas (TCGA) and NCBI’s Gene Expression Omnibus (GEO) in humans. Users can explore not only the expression values of mature individual tRNAs in the human genome, but also those of isodecoders and isoacceptors based on our specific pipelines. DBtRend provides the expressed patterns of tRNAs, the differentially expressed tRNAs in different biological conditions, and the information of samples or patients, tissue types, and molecular subtype of cancers. The database is expected to help researchers interested in functional discoveries of tRNAs.

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 WIND (Workflow for pIRNAs aNd beyonD): a strategy for in-depth analysis of small RNA-seq data

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1
Author(s):  
Konstantinos Geles ◽  
Domenico Palumbo ◽  
Assunta Sellitto ◽  
Giorgio Giurato ◽  
Eleonora Cianflone ◽  
...  
Keyword(s):  
Small Rna ◽  
Differential Expression Analysis ◽  
Small Rna Sequencing ◽  
Rna Seq ◽  
Sequencing Data ◽  
Transcript Quantification ◽  
Annotation Track ◽  
Depth Analysis ◽  
Exploratory Data ◽  
Downstream Analysis

Current bioinformatics workflows for PIWI-interacting RNA (piRNA) analysis focus primarily on germline-derived piRNAs and piRNA-clusters. Frequently, they suffer from outdated piRNA databases, questionable quantification methods, and lack of reproducibility. Often, pipelines specific to miRNA analysis are used for the piRNA research in silico. Furthermore, the absence of a well-established database for piRNA annotation, as for miRNA, leads to uniformity issues between studies and generates confusion for data analysts and biologists. For these reasons, we have developed WIND (Workflow for pIRNAs aNd beyonD), a bioinformatics workflow that addresses the crucial issue of piRNA annotation, thereby allowing a reliable analysis of small RNA sequencing data for the identification of piRNAs and other small non-coding RNAs (sncRNAs) that in the past have been incorrectly classified as piRNAs. WIND allows the creation of a comprehensive annotation track of sncRNAs combining information available in RNAcentral, with piRNA sequences from piRNABank, the first database dedicated to piRNA annotation. WIND was built with Docker containers for reproducibility and integrates widely used bioinformatics tools for sequence alignment and quantification. In addition, it includes Bioconductor packages for exploratory data and differential expression analysis. Moreover, WIND implements a "dual" approach for the evaluation of sncRNAs expression level quantifying the aligned reads to the annotated genome and carrying out an alignment-free transcript quantification using reads mapped to the transcriptome. Therefore, a broader range of piRNAs can be annotated, improving their quantification and easing the subsequent downstream analysis. WIND performance has been tested with several small RNA-seq datasets, demonstrating how our approach can be a useful and comprehensive resource to analyse piRNAs and other classes of sncRNAs.

scholarly journals WIND (Workflow for pIRNAs aNd beyonD): a strategy for in-depth analysis of small RNA-seq data

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1
Author(s):  
Konstantinos Geles ◽  
Domenico Palumbo ◽  
Assunta Sellitto ◽  
Giorgio Giurato ◽  
Eleonora Cianflone ◽  
...  
Keyword(s):  
Small Rna ◽  
Differential Expression Analysis ◽  
Small Rna Sequencing ◽  
Rna Seq ◽  
Sequencing Data ◽  
Transcript Quantification ◽  
Annotation Track ◽  
Depth Analysis ◽  
Exploratory Data ◽  
Downstream Analysis

Current bioinformatics workflows for PIWI-interacting RNA (piRNA) analysis focus primarily on germline-derived piRNAs and piRNA-clusters. Frequently, they suffer from outdated piRNA databases, questionable quantification methods, and lack of reproducibility. Often, pipelines specific to miRNA analysis are used for the piRNA research in silico. Furthermore, the absence of a well-established database for piRNA annotation, as for miRNA, leads to uniformity issues between studies and generates confusion for data analysts and biologists. For these reasons, we have developed WIND (Workflow for pIRNAs aNd beyonD), a bioinformatics workflow that addresses the crucial issue of piRNA annotation, thereby allowing a reliable analysis of small RNA sequencing data for the identification of piRNAs and other small non-coding RNAs (sncRNAs) that in the past have been incorrectly classified as piRNAs. WIND allows the creation of a comprehensive annotation track of sncRNAs combining information available in RNAcentral, with piRNA sequences from piRNABank, the first database dedicated to piRNA annotation. WIND was built with Docker containers for reproducibility and integrates widely used bioinformatics tools for sequence alignment and quantification. In addition, it includes Bioconductor packages for exploratory data and differential expression analysis. Moreover, WIND implements a "dual" approach for the evaluation of sncRNAs expression level quantifying the aligned reads to the annotated genome and carrying out an alignment-free transcript quantification using reads mapped to the transcriptome. Therefore, a broader range of piRNAs can be annotated, improving their quantification and easing the subsequent downstream analysis. WIND performance has been tested with several small RNA-seq datasets, demonstrating how our approach can be a useful and comprehensive resource to analyse piRNAs and other classes of sncRNAs.

scholarly journals Comprehensive analysis of human small RNA sequencing data provides insights into expression profiles and miRNA editing

RNA Biology ◽  
2014 ◽  
Vol 11 (11) ◽  
pp. 1375-1385 ◽  
Author(s):  
Jing Gong ◽  
Yuliang Wu ◽  
Xiantong Zhang ◽  
Yifang Liao ◽  
Vusumuzi Leroy Sibanda ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Small Rna ◽  
Expression Profiles ◽  
Comprehensive Analysis ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
Mirna Editing

scholarly journals WIND (Workflow for pIRNAs aNd beyonD): a strategy for in-depth analysis of small RNA-seq data

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1
Author(s):  
Konstantinos Geles ◽  
Domenico Palumbo ◽  
Assunta Sellitto ◽  
Giorgio Giurato ◽  
Eleonora Cianflone ◽  
...  
Keyword(s):  
Small Rna ◽  
Differential Expression Analysis ◽  
Small Rna Sequencing ◽  
Rna Seq ◽  
Sequencing Data ◽  
Transcript Quantification ◽  
Annotation Track ◽  
Depth Analysis ◽  
Exploratory Data ◽  
Downstream Analysis

Current bioinformatics workflows for PIWI-interacting RNA (piRNA) analysis focus primarily on germline-derived piRNAs and piRNA-clusters. Frequently, they suffer from outdated piRNA databases, questionable quantification methods, and lack of reproducibility. Often, pipelines specific to miRNA analysis are used for the piRNA research in silico. Furthermore, the absence of a well-established database for piRNA annotation, as for miRNA, leads to uniformity issues between studies and generates confusion for data analysts and biologists. For these reasons, we have developed WIND (Workflow for pIRNAs aNd beyonD), a bioinformatics workflow that addresses the crucial issue of piRNA annotation, thereby allowing a reliable analysis of small RNA sequencing data for the identification of piRNAs and other small non-coding RNAs (sncRNAs) that in the past have been incorrectly classified as piRNAs. WIND allows the creation of a comprehensive annotation track of sncRNAs combining information available in RNAcentral, with piRNA sequences from piRNABank, the first database dedicated to piRNA annotation. WIND was built with Docker containers for reproducibility and integrates widely used bioinformatics tools for sequence alignment and quantification. In addition, it includes Bioconductor packages for exploratory data and differential expression analysis. Moreover, WIND implements a "dual" approach for the evaluation of sncRNAs expression level quantifying the aligned reads to the annotated genome and carrying out an alignment-free transcript quantification using reads mapped to the transcriptome. Therefore, a broader range of piRNAs can be annotated, improving their quantification and easing the subsequent downstream analysis. WIND performance has been tested with several small RNA-seq datasets, demonstrating how our approach can be a useful and comprehensive resource to analyse piRNAs and other classes of sncRNAs.

scholarly journals miRAuto: An automated user-friendly MicroRNA prediction tool utilizing plant small RNA sequencing data

2013 ◽  
Vol 35 (4) ◽  
pp. 342-347 ◽  
Author(s):  
Jeongsoo Lee ◽  
Dong-in Kim ◽  
June Hyun Park ◽  
Ik-Young Choi ◽  
Chanseok Shin
Keyword(s):  
Rna Sequencing ◽  
Small Rna ◽  
Small Rna Sequencing ◽  
Prediction Tool ◽  
Sequencing Data ◽  
User Friendly ◽  
Plant Small Rna

scholarly journals Metavisitor, a suite of Galaxy tools for simple and rapid detection and discovery of viruses in deep sequence data

2016 ◽  
Author(s):  
Guillaume Carissimo ◽  
Marius van den Beek ◽  
Juliana Pegoraro ◽  
Kenneth D Vernick ◽  
Christophe Antoniewski
Keyword(s):  
Small Rna ◽  
De Novo ◽  
Sequence Data ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
Viral Genomes ◽  
Bioinformatic Tools ◽  
The Galaxy ◽  
Galaxy Server ◽  
User Friendly

AbstractWe present user-friendly and adaptable software to provide biologists, clinical researchers and possibly diagnostic clinicians with the ability to robustly detect and reconstruct viral genomes from complex deep sequence datasets. A set of modular bioinformatic tools and workflows was implemented as the Metavisitor package in the Galaxy framework. Using the graphical Galaxy workflow editor, users with minimal computational skills can use existing Metavisitor workflows or adapt them to suit specific needs by adding or modifying analysis modules. Metavisitor can be used on our Mississippi server, or can be installed on any Galaxy server instance and a pre-configured Metavisitor server image is provided. Metavisitor works with DNA, RNA or small RNA sequencing data over a range of read lengths and can use a combination of de novo and guided approaches to assemble genomes from sequencing reads. We show that the software has the potential for quick diagnosis as well as discovery of viruses from a vast array of organisms. Importantly, we provide here executable Metavisitor use cases, which increase the accessibility and transparency of the software, ultimately enabling biologists or clinicians to focus on biological or medical questions.

scholarly journals Evaluation of Commercially Available Exosomal Isolation Kits from Human Plasma

2019 ◽  
Author(s):  
Yuzhe Sun ◽  
Hefu Zhen ◽  
Mei Guo ◽  
Jingyu Ye ◽  
Zhili Liu ◽  
...  
Keyword(s):  
Data Quality ◽  
Human Plasma ◽  
Small Rna ◽  
Profile Analysis ◽  
Biological Fluids ◽  
Small Rna Sequencing ◽  
Plasma Samples ◽  
Sequencing Data ◽  
Isolation Methods ◽  
User Friendly

AbstractExosomes are cell-derived lipid bilayer particles which are abundant in biological fluids. Exosome is an emerging source of biomarkers to diagnose various human diseases. Sequencing based exosomal studies could provide a comprehensive view of exosomal RNA and protein. To extracted these inclusions, exosomes should be isolated from the plasma first. Several exosome isolation methods were introduced since the discover of exosome. To promote the clinical application of exosomal inclusions, different isolation methods should be compared. We isolated exosomes from human plasma by using user-friendly and commercially available kits, SBI ExoQuick and QIAGEN exoRNeasy. Subsequently, small RNA sequencing was performed with two groups of isolated exosome samples and one group of plasma samples. No fundamental differences of exRNA yield between SC and EQ were found. In RNA profile analysis, the small RNA aligned reads, miRNA pattern, sample clustering varied as a result of methodological differences. Small RNA isolated by ExoQuick presented better data quality and RNA profile than exoRNeasy. This study compared sRNA sequencing data generated from two exosome isolation kits, it provides a reference for future small RNA studies and biomarker prediction in human plasma exosome.

scholarly journals Development of a User-Friendly Pipeline for Mutational Analyses of HIV Using Ultra-Accurate Maximum-Depth Sequencing

Viruses ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1338
Author(s):  
Morgan E. Meissner ◽  
Emily J. Julik ◽  
Jonathan P. Badalamenti ◽  
William G. Arndt ◽  
Lauren J. Mills ◽  
...  
Keyword(s):  
Error Rates ◽  
Maximum Depth ◽  
Sequencing Data ◽  
Background Error ◽  
High Background ◽  
Immunodeficiency Virus ◽  
User Friendly ◽  
Viral Mutagenesis ◽  
Hiv 1

Human immunodeficiency virus type 2 (HIV-2) accumulates fewer mutations during replication than HIV type 1 (HIV-1). Advanced studies of HIV-2 mutagenesis, however, have historically been confounded by high background error rates in traditional next-generation sequencing techniques. In this study, we describe the adaptation of the previously described maximum-depth sequencing (MDS) technique to studies of both HIV-1 and HIV-2 for the ultra-accurate characterization of viral mutagenesis. We also present the development of a user-friendly Galaxy workflow for the bioinformatic analyses of sequencing data generated using the MDS technique, designed to improve replicability and accessibility to molecular virologists. This adapted MDS technique and analysis pipeline were validated by comparisons with previously published analyses of the frequency and spectra of mutations in HIV-1 and HIV-2 and is readily expandable to studies of viral mutation across the genomes of both viruses. Using this novel sequencing pipeline, we observed that the background error rate was reduced 100-fold over standard Illumina error rates, and 10-fold over traditional unique molecular identifier (UMI)-based sequencing. This technical advancement will allow for the exploration of novel and previously unrecognized sources of viral mutagenesis in both HIV-1 and HIV-2, which will expand our understanding of retroviral diversity and evolution.

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