Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration.

Data visualization is an essential component of genomic data analysis. However, the size and diversity of the data sets produced by today's sequencing and array-based profiling methods present major challenges to visualization tools. The Integrative Genomics Viewer (IGV) is a high-performance viewer that efficiently handles large heterogeneous data sets, while providing a smooth and intuitive user experience at all levels of genome resolution. A key characteristic of IGV is its focus on the integrative nature of genomic studies, with support for both array-based and next-generation sequencing data, and the integration of clinical and phenotypic data. Although IGV is often used to view genomic data from public sources, its primary emphasis is to support researchers who wish to visualize and explore their own data sets or those from colleagues. To that end, IGV supports flexible loading of local and remote data sets, and is optimized to provide high-performance data visualization and exploration on standard desktop systems. IGV is freely available for download from http://www.broadinstitute.org/igv, under a GNU LGPL open-source license

Seven clusters of data visualization articles in Scopus using social network analysis

The aim of this study was to analyse the bibliographic characteristics and content of articles on Data Visualization published in journals indexed by Scopus written by researchers from throughout the world. We conducted a bibliometric and content analysis of publication in the Scopus database. We only retrieved articles written in English. We conducted content analysis using the VOSviewer software and visualized the co-occurrence of keywords and bibliographic coupling of sources and countries. Following the study protocol, we found 862 articles on Data Visualization over the past 30 years. The most productive journal that published these articles was Lecture Notes In Computer Science (n=32). The most productive country was the United States (n=305). Based on citations, the most influential authors, and journals were Thorvaldsdóttir et al., (2013) [Thorvaldsdóttir, H., Robinson, J. T., & Mesirov, J. P. (2013). Integrative Genomics Viewer (IGV): High-performance genomics data visualization and exploration. Briefings in Bioinformatics, 14(2), 178–192.] (n=4699), and IEE Transactions on Visualization and Computer Graphics (n=656). The keywords of research on Data Visualization formed 7 clusters (e.g. Data Visualization, Visualization, and Human). From a global perspective, Data Visualization research in the past 30 years has increased significantly. There were European published journals nominated publications. Thus, Asian countries need to conduct more active research on this topic

Sashimi plots: Quantitative visualization of RNA sequencing read alignments

We introduce Sashimi plots, a quantitative multi-sample visualization of mRNA sequencing reads aligned to gene annotations. Sashimi plots are made using alignments (stored in the SAM/BAM format) and gene model annotations (in GFF format), which can be custom-made by the user or obtained from databases such as Ensembl or UCSC. We describe two implementations of Sashimi plots: (1) a stand-alone command line implementation aimed at making customizable publication quality figures, and (2) an implementation built into the Integrated Genome Viewer (IGV) browser, which enables rapid and dynamic creation of Sashimi plots for any genomic region of interest, suitable for exploratory analysis of alternatively spliced regions of the transcriptome. Isoform expression estimates outputted by the MISO program can be optionally plotted along with Sashimi plots. Sashimi plots can be used to quickly screen differentially spliced exons along genomic regions of interest and can be used in publication quality figures. The Sashimi plot software and documentation is available from: http://genes.mit.edu/burgelab/miso/docs/sashimi.htmlComment: 2 figure

MEXPRESS : visualizing expression, DNA methylation and clinical TCGA data

Background: In recent years, increasing amounts of genomic and clinical cancer data have become publically available through large-scale collaborative projects such as The Cancer Genome Atlas (TCGA). However, as long as these datasets are difficult to access and interpret, they are essentially useless for a major part of the research community and their scientific potential will not be fully realized. To address these issues we developed MEXPRESS, a straightforward and easy-to-use web tool for the integration and visualization of the expression, DNA methylation and clinical TCGA data on a single-gene level (http://mexpress.be). Results: In comparison to existing tools, MEXPRESS allows researchers to quickly visualize and interpret the different TCGA datasets and their relationships for a single gene, as demonstrated for GSTP1 in prostate adenocarcinoma. We also used MEXPRESS to reveal the differences in the DNA methylation status of the PAM50 marker gene MLPH between the breast cancer subtypes and how these differences were linked to the expression of MPLH. Conclusions: We have created a user-friendly tool for the visualization and interpretation of TCGA data, offering clinical researchers a simple way to evaluate the TCGA data for their genes or candidate biomarkers of interest

BioVLAB-MMIA-NGS: MicroRNA-mRNA Integrated Analysis using High Throughput Sequencing Data

Motivation: It is now well established that microRNAs (miRNAs) play a critical role in regulating gene expression in a sequence-specific manner, and genome-wide efforts are underway to predict known and novel miRNA targets. However, the integrated miRNA–mRNA analysis remains a major computational challenge, requiring powerful informatics systems and bioinformatics expertise. Results: The objective of this study was to modify our widely recognized Web server for the integrated mRNA–miRNA analysis (MMIA) and its subsequent deployment on the Amazon cloud (BioVLAB-MMIA) to be compatible with high-throughput platforms, including next-generation sequencing (NGS) data (e.g. RNA-seq). We developed a new version called the BioVLAB-MMIA-NGS, deployed on both Amazon cloud and on a high-performance publicly available server called MAHA. By using NGS data and integrating various bioinformatics tools and databases, BioVLAB-MMIA-NGS offers several advantages. First, sequencing data is more accurate than array-based methods for determining miRNA expression levels. Second, potential novel miRNAs can be detected by using various computational methods for characterizing miRNAs. Third, because miRNA-mediated gene regulation is due to hybridization of an miRNA to its target mRNA, sequencing data can be used to identify many-to-many relationship between miRNAs and target genes with high accuracy

NGS compatible streamlined DNA recovery from 3D cell cultures in GrowDex®

Here, we describe a streamlined workflow for constructing an NGS whole exome sequencing (WES) from a low amount of PDCs grown as spheroids in GrowDex.Non peer reviewe

A common phytoene synthase mutation underlies white petal varieties of the California poppy.

The California poppy (Eschscholzia californica) is renowned for its brilliant golden-orange flowers, though white petal variants have been described. By whole-transcriptome sequencing, we have discovered in multiple white petal varieties a single deletion leading to altered splicing and C-terminal truncation of phytoene synthase (PSY), a key enzyme in carotenoid biosynthesis. Our findings underscore the diverse roles of phytoene synthase in shaping horticultural traits, and resolve a longstanding mystery of the regaled golden poppy

PLAZA 4.0 : an integrative resource for functional, evolutionary and comparative plant genomics

PLAZA (https://bioinformatics.psb.ugent.be/plaza) is a plant-oriented online resource for comparative, evolutionary and functional genomics. The PLAZA platform consists of multiple independent instances focusing on different plant clades, while also providing access to a consistent set of reference species. Each PLAZA instance contains structural and functional gene annotations, gene family data and phylogenetic trees and detailed gene colinearity information. A user-friendly web interface makes the necessary tools and visualizations accessible, specific for each data type. Here we present PLAZA 4.0, the latest iteration of the PLAZA framework. This version consists of two new instances (Dicots 4.0 and Monocots 4.0) providing a large increase in newly available species, and offers access to updated and newly implemented tools and visualizations, helping users with the ever-increasing demands for complex and in-depth analyzes. The total number of species across both instances nearly doubles from 37 species in PLAZA 3.0 to 71 species in PLAZA 4.0, with a much broader coverage of crop species (e.g. wheat, palm oil) and species of evolutionary interest (e.g. spruce, Marchantia). The new PLAZA instances can also be accessed by a programming interface through a RESTful web service, thus allowing bioinformaticians to optimally leverage the power of the PLAZA platform

Cytoscape: the network visualization tool for GenomeSpace workflows.

Modern genomic analysis often requires workflows incorporating multiple best-of-breed tools. GenomeSpace is a web-based visual workbench that combines a selection of these tools with mechanisms that create data flows between them. One such tool is Cytoscape 3, a popular application that enables analysis and visualization of graph-oriented genomic networks. As Cytoscape runs on the desktop, and not in a web browser, integrating it into GenomeSpace required special care in creating a seamless user experience and enabling appropriate data flows. In this paper, we present the design and operation of the Cytoscape GenomeSpace app, which accomplishes this integration, thereby providing critical analysis and visualization functionality for GenomeSpace users. It has been downloaded over 850 times since the release of its first version in September, 2013