TrioVis 20130409 – Visualization approach for Filtering Genomic Variants of Parent-child Trios

TrioVis 20130409

:: DESCRIPTION

TrioVis is a visualisation tool developed to assist filtering on coverage and variant frequency for genomic variants from exome sequencing of parent-child trios. It organises the variant data by grouping each variant based on the laws of Mendelian inheritance. Taking three Variant Call Format (VCF) files as input, the tool provides a user interface to test different coverage thresholds (i.e. different levels of stringency), to find the optimal threshold values, and to gain insights into the global effects of filtering.

::DEVELOPER

Bioinformatics Research Group, Belgium

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Java

:: DOWNLOAD

TrioVis

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Jul 15;29(14):1801-2. doi: 10.1093/bioinformatics/btt267. Epub 2013 May 8.
TrioVis: a visualization approach for filtering genomic variants of parent-child trios.
Sakai R, Sifrim A, Vande Moere A, Aerts J.

pviz 0.1.12 – Dynamic JavaScript & SVG library for Visualization of Protein Sequence Features

pviz 0.1.12

:: DESCRIPTION

pViz.js is a visualization library for displaying protein sequence features in a web browser

::DEVELOPER

pviz team

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Java

:: DOWNLOAD

 pviz

 :: MORE INFORMATION

Citation

Visualization of protein sequence features using JavaScript and SVG with pViz.js.
Mukhyala K, Masselot A.
Bioinformatics. 2014 Aug 21. pii: btu567.

OLIN 1.68.0 – Optimized Normalization, Visualization and Quality Testing of two-channel Microarray data

OLIN 1.68.0

:: DESCRIPTION

OLIN (Optimised Local Intensity-dependent Normalisation) is the software developed for optimized normalization.

::DEVELOPER

SysBioLab

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R package
  • BioConductor
  • R-TclTk

:: DOWNLOAD

 OLIN

:: MORE INFORMATION

Citation

Bioinformatics. 2005 Apr 15;21(8):1724-6.
OLIN: optimized normalization, visualization and quality testing of two-channel microarray data.
Futschik ME, Crompton T.

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

:: 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.

SAVoR – Sequencing Annotation and Visualization of RNA structures

SAVoR

:: DESCRIPTION

SAVoR is an easy-to-use web application that allows the user to visualize RNA-seq data and other genomic annotations on RNA secondary structures. SAVoR is designed to help researchers visualize sequencing data in the context of RNA secondary structures.

::DEVELOPER

 Wang Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

SAVoR: a server for sequencing annotation and visualization of RNA structures.
Li F, Ryvkin P, Childress DM, Valladares O, Gregory BD, Wang LS.
Nucleic Acids Res. 2012 Jul;40(Web Server issue):W59-64. doi: 10.1093/nar/gks310.

Clustergrammer 1.19.5 – Web-based Heatmap Visualization and Analysis Tool for High-Dimensional Biological Data

Clustergrammer 1.19.5

:: DESCRIPTION

Clustergrammer is a web-based visualization tool with interactive features such as: zooming, panning, filtering, reordering, sharing, performing enrichment analysis, and providing dynamic gene annotations.

::DEVELOPER

Ma’ayan Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

Clustergrammer

:: MORE INFORMATION

Citation

Sci Data. 2017 Oct 10;4:170151. doi: 10.1038/sdata.2017.151.
Clustergrammer, a web-based heatmap visualization and analysis tool for high-dimensional biological data.
Fernandez NF, Gundersen GW, Rahman A, Grimes ML, Rikova K, Hornbeck P, Ma’ayan A.

L1000FWD – Large-scale Visualization of Drug-induced Transcriptomic Signatures

L1000FWD

:: DESCRIPTION

L1000FWD (L1000 fireworks display) is a web application that provides interactive visualization of over 16,000 drug and small-molecule induced gene expression signatures.

::DEVELOPER

Ma’ayan Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Bioinformatics. 2018 Jun 15;34(12):2150-2152. doi: 10.1093/bioinformatics/bty060.
L1000FWD: fireworks visualization of drug-induced transcriptomic signatures.
Wang Z, Lachmann A, Keenan AB, Ma’ayan A.

SNAVI 20081120 – Analysis and Visualization of Large-Scale Cell Signaling Networks

SNAVI 20081120

:: DESCRIPTION

SNAVI (Signaling Networks Analysis and Visualization) is a Windows-based desktop application that implements standard network analysis methods to compute the clustering, connectivity distribution, and detection of network motifs, as well as provides means to visualize networks and network motifs. SNAVI is capable of generating linked web pages from network datasets loaded in text format. SNAVI can also create networks from lists of gene or protein names. SNAVI is a useful tool for analyzing, visualizing and sharing cell signaling data. SNAVI is open source free software.

::DEVELOPER

Ma’ayan Laboratory

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 SNAVI

:: MORE INFORMATION

Citation

BMC Syst Biol. 2009 Jan 20;3:10. doi: 10.1186/1752-0509-3-10.
SNAVI: Desktop application for analysis and visualization of large-scale signaling networks.
Ma’ayan A, Jenkins SL, Webb RL, Berger SI, Purushothaman SP, Abul-Husn NS, Posner JM, Flores T, Iyengar R.

dChip 2011.12 – Analysis & Visualization of Gene Expression & SNP Microarrays

dChip 2011.12

:: DESCRIPTION

DNA-Chip Analyzer (dChip) is a Windows software package for probe-level (e.g. Affymetrix platform) and high-level analysis of gene expression microarrays and SNP microarrays.

Gene expression or SNP data from various microarray platforms can also be analyzed by importing as external dataset. At the probe level, dChip can display and normalize the CEL files, and the model-based approach allows pooling information across multiple arrays and automatic probe selection to handle cross-hybridization and image contamination. High-level analysis in dChip includes comparing samples, hierarchical clustering, view expression and SNP data along chromosome, LOH and copy number analysis of SNP arrays, and linkage analysis. In these functions the gene information and sample information are correlated with the analysis results.

::DEVELOPER

Started in Wing Wong Lab , Developed & Maintained by Cheng Li Lab.

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows
  • Linux with Wine
  • Mac with Virtual PC

:: DOWNLOAD

dChip

:: MORE INFORMATION

Please cite Li and Wong 2001a if dChip results are used in manuscripts, and cite Lin et al. 2004 if dChip SNP analysis functions are used.

VANESA 0.3 – Visualization and Analysis of Networks in System Biology

VANESA 0.3

:: DESCRIPTION

VANESA is a software application for the visualization and analysis of biomedical networks in system biology applications to create systems that can answer fundamental questions and moreover, imitate cell behavior.

::DEVELOPER

the Bioinformatics / Medical Informatics department at Bielefeld University.

:: SCREENSHOTS

:: REQUIREMENTS

  •  Linux / Windows/ MacOsX
  • Java

:: DOWNLOAD

 VANESA

:: MORE INFORMATION

Citation

VANESA – a software application for the visualization and analysis of networks in system biology applications.
Brinkrolf C, Janowski SJ, Kormeier B, Lewinski M, Hippe K, Borck D, Hofestädt R.
J Integr Bioinform. 2014 Jun 23;11(2):239. doi: 10.2390/biecoll-jib-2014-239.