GenVisR 1.16.1 – Genome Data Visualizations

GenVisR 1.16.1

:: DESCRIPTION

Intuitively visualizing and interpreting data from high-throughput genomic technologies continues to be challenging.GenVisR (“Genomic Visualizations in R”) attempts to alleviate this burden by providing highly customizable publication-quality graphics supporting multiple species and focused primarily on a cohort level (i.e., multiple samples/patients). GenVisR attempts to maintain a high degree of flexibility while leveraging the abilities of ggplot2 and bioconductor to achieve this goal.

::DEVELOPER

The Griffith Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX / Windows
  • R/ BioConductor

:: DOWNLOAD

 GenVisR

:: MORE INFORMATION

Citation

GenVisR: Genomic Visualizations in R.
Skidmore ZL, Wagner AH, Lesurf R, Campbell KM, Kunisaki J, Griffith OL, Griffith M.
Bioinformatics. 2016 Jun 10. pii: btw325.

IGB 9.0.2 – Visualization for Genome-scale Data

IGB 9.0.2

:: DESCRIPTION

IGB (Integrated Genome Browser) is an interactive, zoomable, scrollable software program you can use to visualize and explore genome-scale data sets, such as tiling array data, next-generation sequencing results, genome annotations, microarray designs, and the sequence itself.

::DEVELOPER

IGB team Department of Bioinformatics and Genomics, University of North Carolina at Charlotte

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows / Mac OsX
  • Java

:: DOWNLOAD

IGB

:: MORE INFORMATION

Citation:

Nicol JW, Helt GA, Blanchard SG Jr, Raja A, Loraine AE.
The Integrated Genome Browser: free software for distribution and exploration of genome-scale datasets.
Bioinformatics. 2009 Oct 15;25(20):2730-1.

caOmicsV 1.14.0 – Visualization of Multi-dimentional Cancer Genomics data

caOmicsV 1.14.0

:: DESCRIPTION

caOmicsV package provides methods to visualize multi-dimentional cancer genomics data including of patient information, gene expressions, DNA methylations, DNA copy number variations, and SNP/mutations in matrix layout or network layout.

::DEVELOPER

Henry Zhang <hzhang at mail.nih.gov>

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux / Windows/ MacOsX
  • R / BioConductor

:: DOWNLOAD

 caOmicsV

:: MORE INFORMATION

Citation

caOmicsV: an R package for visualizing multidimensional cancer genomic data.
Zhang H, Meltzer PS, Davis SR.
BMC Bioinformatics. 2016 Mar 22;17(1):141. doi: 10.1186/s12859-016-0989-6.

TASUKE ver.20190826 – Visualization program for Large-scale Resequencing data

TASUKE ver.20190826

:: DESCRIPTION

TASUKE is a web application that visualizes large-scale resequencing data generated by next-generation sequencing technologies.The variation and read depth of multiple genomes, as well as annotations, can be shown simultaneously at various scales.

::DEVELOPER

Bioinformatics Research Unit, Agrogenomics Research Center

:: SCREENSHOTS

TASUKE

:: REQUIREMENTS

  • Linux
  • Apach
  • Php
  • MySQL

:: DOWNLOAD

 TASUKE

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Jul 15;29(14):1806-8. doi: 10.1093/bioinformatics/btt295. Epub 2013 Jun 7.
TASUKE: a web-based visualization program for large-scale resequencing data.
Kumagai M1, Kim J, Itoh R, Itoh T.

Cytoscape 3.7.2 – Platform for Complex-Network Analysis & Visualization

Cytoscape 3.7.2

:: DESCRIPTION

Cytoscape is an open source bioinformatics software platform for visualizing molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.

Although Cytoscape was originally designed for biological research, now it is a general platform for complex network analysis and visualization.

::DEVELOPER

Cytoscape Team

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Java

:: DOWNLOAD

Cytoscape

:: MORE INFORMATION

Citation:

Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T.
Cytoscape: a software environment for integrated models of biomolecular interaction networks.
Genome Research 2003 Nov; 13(11):2498-504

ReadXplorer 2.2.3 – Visualization and Analysis of Mapped Sequences

ReadXplorer 2.2.3

:: DESCRIPTION

ReadXplorer is a freely available comprehensive exploration and evaluation tool for NGS data. It extracts and adds quantity and quality measures to each alignment in order to classify the mapped reads. This classification is then taken into account for the different data views and all supported automatic analysis functions.

::DEVELOPER

Bioinformatics and Systems Biology, Justus-Liebig-University

:: SCREENSHOTS

ReadXplorer

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Java

:: DOWNLOAD

 ReadXplorer

:: MORE INFORMATION

Citation

Bioinformatics. 2014 Apr 30. [Epub ahead of print]
ReadXplorer – Visualization and Analysis of Mapped Sequences.
Hilker R, Stadermann KB, Doppmeier D, Kalinowski J, Stoye J, Straube J, Winnebald J, Goesmann A.

GMOL 2 – 3D Genome Structure Visualization

GMOL 2

:: DESCRIPTION

GMOL is an application designed to visualize genome structure in 3D. It allows users to view the genome structure at multiple scales, including: global, chromosome, loci, fiber, nucleosome, and nucleotide.

::DEVELOPER

Dr. Jianlin Cheng’s Bioinformatics and Systems Biology Laboratory

:: SCREENSHOTS

GMOL

:: REQUIREMENTS

  • Linux/ Windows/ MacOsX
  • Java

:: DOWNLOAD

 GMOL

:: MORE INFORMATION

Genonets – Analysis and Visualization of Genotype Networks

Genonets

:: DESCRIPTION

Genonets Server is a tool that provides the following features: (i) the construction of genotype networks for categorical and univariate phenotypes from DNA, RNA, amino acid or binary sequences; (ii) analyses of genotype network topology and how it relates to robustness and evolvability, as well as analyses of genotype network topography and how it relates to the navigability of a genotype network via mutation and natural selection; (iii) multiple interactive visualizations that facilitate exploratory research and education.

::DEVELOPER

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Genonets server-a web server for the construction, analysis and visualization of genotype networks.
Khalid F, Aguilar-Rodríguez J, Wagner A, Payne JL.
Nucleic Acids Res. 2016 Apr 22. pii: gkw313.

LookSeq 2 – Alignment Visualization, Browsing and Analysis of Genome Sequence data

LookSeq 2

:: DESCRIPTION

LookSeq supports multiple sequencing technologies, alignment sources, and viewing modes; low or high-depth read pileups; and easy visualization of putative single nucleotide and structural variation. The visible range, from whole chromosome to single base resolution, can be set manually or by scrolling or zooming the display with fast, on-the-fly rendering from the server-side alignment database. LookSeq uses a universal database for alignments of different sequencing technologies and algorithms. Sequence data from multiple sources can be viewed separately or aligned in a single display, facilitating direct comparison between datasets. LookSeq can also link to relevant external sites such as PubMed and other online analysis tools, via buttons or double-clicking on the displayed sequence annotation

lookseq Online Version

::DEVELOPER

Dr Magnus ManskeWellcome Trust Sanger Institute

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • WebServer
  • Perl

:: DOWNLOAD

 LookSeq

:: MORE INFORMATION

Citation

Genome Res. 2009 Nov;19(11):2125-32. Epub 2009 Aug 13.
LookSeq: a browser-based viewer for deep sequencing data.
Manske HM, Kwiatkowski DP.

SeqGrapheR 0.4.8.5 – Graph based Visualization of Cluster of DNA sequence reads

SeqGrapheR 0.4.8.5

:: DESCRIPTION

 SeqGrapheR package provide interactive GUI for visualization of DNA sequence clusters.

::DEVELOPER

Laboratory of Molecular CytogeneticsInstitute of Plant Molecular Biology ,Biology Centre ASCR

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R package

:: DOWNLOAD

 SeqGrapheR

:: MORE INFORMATION

Citation

Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data
Petr Novák, Pavel Neumann and Jiří Macas
BMC Bioinformatics 2010, 11:378