PGS – Analyzing Associations of high-dimensional microRNA Expression data

PGS

:: DESCRIPTION

PGS (Penalized GEE with Grid Search) is a penalized regression model incorporating grid search method for analyzing associations of high-dimensional microRNA expression data with repeated measures.

::DEVELOPER

PGS team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows/ MacOsX
  • R

:: DOWNLOAD

 PGS

:: MORE INFORMATION

Citation

PGS: a tool for association study of high-dimensional microRNA expression data with repeated measures.
Zheng Y, Fei Z, Zhang W, Starren JB, Liu L, Baccarelli A, Li Y, Hou L.
Bioinformatics. 2014 Jun 19. pii: btu396.

CLUTO 2.1.2a / gCLUTO 1.0 – Software for Clustering High-Dimensional Datasets

CLUTO 2.1.2a / gCLUTO 1.0

:: DESCRIPTION

CLUTO is a software package for clustering low- and high-dimensional datasets and for analyzing the characteristics of the various clusters. CLUTO is well-suited for clustering data sets arising in many diverse application areas including information retrieval, customer purchasing transactions, web, GIS, science, and biology.

gCLUTO is a cross-platform graphical application for clustering low- and high-dimensional datasets and for analyzing the characteristics of the various clusters.

::DEVELOPER

Karypis Lab

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux/ Windows

:: DOWNLOAD

 CLUTO  / gCLUTO

:: MORE INFORMATION

Citation:

Matt Rasmussen and George Karypis.
gCLUTO: An Interactive Clustering, Visualization, and Analysis System.
UMN-CS TR-04-021, 2004.

LAS – Finding Large Average Submatricies in High Dimensional Data

LAS

:: DESCRIPTION

LAS (Large Average Submatricies) is a statistically motivated biclustering method that finds large average submatrices within a given real-valued data matrix

::DEVELOPER

Andrey A. Shabalin

:: SCREENSHOTS

::REQUIREMENTS

:: DOWNLOAD

 LAS

:: MORE INFORMATION

Citation

Andrey A. Shabalin et al.
Finding Large Average Submatricies in High Dimensional Data
Annals of Applied Statistics 2009, Vol. 3, No. 3, 985-1012

GemStone 1.0 – Analysis of High-dimensional, Flow Cytometry Data

GemStone 1.0

:: DESCRIPTION

GemStone is a revolutionary new paradigm for analysis of high-dimensional, flow cytometry data.
Based on patented Probability State Modeling* technology, GemStone eliminates the problems that have faced flow cytometry analysis for decades, providing a solution that is science-based, data-driven, scalable, and reproducible.

::DEVELOPER

Verity Software House

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Mac OsX

:: DOWNLOAD

GemStone

:: MORE INFORMATION

Price