GenePattern 3.9.11 – Genomic Analysis Platform

GenePattern 3.9.11

:: DESCRIPTION

GenePattern is a powerful genomic analysis platform that provides access to more than 125 tools for gene expression analysis, proteomics, SNP analysis and common data processing tasks. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research.

GenePattern provides access to a broad array of computational methods used to analyze genomic data. Its extendable architecture makes it easy for computational biologists to add analysis and visualization modules, which ensures that GenePattern users have access to new computational methods on a regular basis.

::DEVELOPER

The GenePattern team

:: SCREENSHOTS

:: REQUIREMENTS

  • Java VM
  • MacOSX/Windows/Linux
  • Other Java-enabled Platforms

:: DOWNLOAD

GenePattern

:: MORE INFORMATION

Citation

ATARiS: computational quantification of gene suppression phenotypes from multisample RNAi screens.
Shao DD, Tsherniak A, Gopal S, Weir BA, Tamayo P, Stransky N, Schumacher SE, Zack TI, Beroukhim R, Garraway LA, Margolin AA, Root DE, Hahn WC, Mesirov JP.
Genome Res. 2013 Apr;23(4):665-78. doi: 10.1101/gr.143586.112.

Reich M, Liefeld T, Gould J, Lerner J, Tamayo P, Mesirov JP
GenePattern 2.0
Nature Genetics 38 no. 5 (2006): pp500-501

Haploview 4.2 – Analysis & Visualization of LD & Haplotype Maps

Haploview 4.2

:: DESCRIPTION

Haploview is designed to simplify and expedite the process of haplotype analysis by providing a common interface to several tasks relating to such analyses.

::DEVELOPER

The Analytic and Translational Genetics Unit(AUGT),The Broad Institute,

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Java

:: DOWNLOAD

Haploview

:: MORE INFORMATION

Citation

Barrett JC, Fry B, Maller J, Daly MJ.
Haploview: analysis and visualization of LD and haplotype maps.
Bioinformatics. 2005 Jan 15 [PubMed ID: 15297300]

ProDy 1.10.10 – Python package for Analysis and Modeling of Protein Structural Dynamics

ProDy 1.10.10

:: DESCRIPTION

ProDy is a free and open-source Python package for analysis and modeling of protein structural dynamics. It allows for efficient analysis of large datasets and is suitable for development or prototyping of structure-based analysis and modeling software.

::DEVELOPER

Bahar lab

:: SCREENSHOTS

N/A

: REQUIREMENTS

:: DOWNLOAD

 ProDy

:: MORE INFORMATION

Citation:

Bakan A, Meireles LM, Bahar I
ProDy: Protein Dynamics Inferred from Theory and Experiments
Bioinformatics 2011 27(11):1575-1577.

PowerMarker 3.25 – Statistical Software for Genetic Marker data analysis

PowerMarker 3.25

:: DESCRIPTION

PowerMarker is a comprehensive set of statistical methods for genetic marker data analysis, designed especially for SSR/SNP data analysis. PowerMarker builds a powerful user interface around both new and traditional statistical methods for population genetic analysis.

::DEVELOPER

Jack Liu

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

 PowerMarker

:: MORE INFORMATION

Citation

Bioinformatics. 2005 May 1;21(9):2128-9. Epub 2005 Feb 10.
PowerMarker: an integrated analysis environment for genetic marker analysis.
Liu K, Muse SV.

CummeRbund 2.28.0 – Exploration, Analysis and Visualization of Cufflinks high-throughput RNA-Seq data

CummeRbund 2.28.0

:: DESCRIPTION

CummeRbund is an R package that is designed to aid and simplify the task of analyzing Cufflinks RNA-Seq output.CummeRbund was designed to help simplify the analysis and exploration portion of RNA-Seq data derrived from the output of a differential expression analysis using cuffdiff with the goal of providing fast and intuitive access to your results.

::DEVELOPER

Kellis Lab &  the Rinn Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • R package
  • Bioconductor

:: DOWNLOAD

 CummeRbund

:: MORE INFORMATION

Citation

Nat Protoc. 2012 Mar 1;7(3):562-78. doi: 10.1038/nprot.2012.016.
Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks.
Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, Pimentel H, Salzberg SL, Rinn JL, Pachter L.

MAVisto 2.7.0 – Motif Analysis and VISualisation TOolkit

MAVisto 2.7.0

:: DESCRIPTION

MAVisto (Motif Analysis and VISualisation TOolkit)is a tool for the exploration of motifs in network. It provides a flexible motif search algorithm and different views for the analysis and visualisation of network motifs.

::DEVELOPER

Life Science Informatics – Prof. Dr. Falk Schreiber

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Linux/  MacOSX
  • Java

:: DOWNLOAD

 MAVisto

:: MORE INFORMATION

Citation

Schreiber, F. and Schwöbbermeyer H.
MAVisto: a tool for the exploration of network motifs.
Bioinformatics, 21, 3572-3574, 2005.

ARTO – Analysis of Replication Timing and Organization

ARTO

:: DESCRIPTION

ARTO (Analysis of Replication Timing and Organization) uses signal processing methods to fit a constant piece-wise linear curve to the measured raw data. The software takes raw time of replication (ToR) measurement signals as input and outputs for each genomic location an estimate of its ToR and an association to CTR (constant ToR region) or TTR (Temporal Transition Region).

::DEVELOPER

Laboratory of Computational Biology at the Technion.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • MatLab

:: DOWNLOAD

  ARTO

:: MORE INFORMATION

Citation

Systematic determination of replication activity type highlights interconnections between replication, chromatin structure and nuclear localization.
Farkash-Amar S, David Y, Polten A, Hezroni H, Eldar YC, Meshorer E, Yakhini Z, Simon I.
PLoS One. 2012;7(11):e48986.

LPIA v1 – Latent Pathway Identification Analysis

LPIA v1

:: DESCRIPTION

LPIA is a computational method for identifying biological pathways as putative sources of transcriptional dysregulation. It looks for statistically signficant evidence of dysregulation in a network of pathways constructed in a manner that explicitly links pathways through their common function in the cell.

::DEVELOPER

Eric D. Kolaczyk

:: SCREENSHOTS

n/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • Perl

:: DOWNLOAD

 LPIA

:: MORE INFORMATION

Citation

Pham, L., Christadore, L., Schaus, S., and Kolaczyk, E.D. (2011).
Network-based prediction for sources of transcriptional dysregulation via latent pathway identification analysis.
Proceedings of the National Academy of Sciences, doi: 10.1073/pnas.1100891108.

SAMMate 2.7.4 / assemblySAM 1.1 – Processing Short Read Alignments in SAM/BAM format / RNA-Seq Assembly and Analysis

SAMMate 2.7.4 / assemblySAM 1.1

:: DESCRIPTION

SAMMate is an open source GUI software suite to process RNA-Seq data. It is composed of two modules: assemblySAM and SAMMate.

assemblySAM employs a novel method to localize and assemble RNA-seq reads into RNA transcript sequences.

::DEVELOPER

Dongxiao Zhu, Ph.D

:: SCREENSHOTS

sammate

:: REQUIREMENTS

  • Linux/ Windows/MacOsX
  • Java
  • R package

:: DOWNLOAD

 SAMMate / assemblySAM

:: MORE INFORMATION

Citation:

Source Code Biol Med. 2011 Jan 13;6(1):2. doi: 10.1186/1751-0473-6-2.
SAMMate: a GUI tool for processing short read alignments in SAM/BAM format.
Xu G1, Deng N, Zhao Z, Judeh T, Flemington E, Zhu D.

Nguyen, T, Zhao, Z, Zhu, D.
SPATA: A seeding and patching algorithm for hybrid transcriptome assembly.

Nguyen, T, Deng, N, Zhu, D.
SASeq: A selective and adaptive shrinkage approach to detect and quantify active transcripts using RNA-Seq.

BIANA 1.4.5 – Biologic Interaction and Network Analysis

BIANA 1.4.5

:: DESCRIPTION

BIANA (Biologic Interactions and Network Analysis) is a biological database integration and network management framework written in Python. It uses a high level abstraction schema to define databases providing any kind of biological information (both individual entries and their relationships).

::DEVELOPER

Structural BioInformatics Lab

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

 BIANA

:: MORE INFORMATION

Citation

Biana: a software framework for compiling biological interactions and analyzing networks.
Garcia-Garcia J, Guney E, Aragues R, Planas-Iglesias J, Oliva B.
BMC Bioinformatics. 2010 Jan 27;11:56.