Search Results for "network data speed"

In metabolomics the goal is to identify and measure the concentrations of different metabolites (small molecules) in a cell or a biological system. The metabolites form an important layer in the complex metabolic network, and the interactions between different metabolites are often of interest. It is crucial to perform proper normalization of metabolomics data and here we share the code for a normalization approach based on a mixed model, with simultaneous estimation of a correlation matrix. The methodology is implemented in R.

RIPE (Regulatory network Inference from joint Perturbation and Expression data) is a novel three-step method that integrates both perturbation data and steady state gene expression data in order to estimate a regulatory network. The ripe package is written in R, with additional functionality provided by a MATLAB executable file. The executable file uses a runtime engine called the MATLAB Compiler Runtime (MCR).

MCPerm: A Monte Carlo permutation method for multiple test correlation in case-control association study Traditional permutation (TradPerm) test is an important non-parametric analysis method which can be treated as the gold standard for multiple testing corrections in case-control association study. However, it relies on the original single nucleotide polymorphism (SNP) genotypes and phenotypes data to perform a large number of random shuffles, and thus it is computationally intensive, especially for genome-wide association study (GWAS). To improve the calculation speed without changing the size of the TradPerm p-value, we developed a Monte Carlo permutation (MCPerm) method as an efficient alternative to TradPerm. Methods: MCPerm does not need to shuffle the original genotypes and phenotypes data.

You may also like some newer work: http://createdatasol.com/ Project imDEV is an application of RExcel, which seamlessly integrates Excel and R for tasks focused on multivariate data visualization, exploration, and analysis. Interactive modules for dimensional reduction (imPCA), prediction (imPLS), feature selection, analysis of correlation (imCorrelations) and generation of networked structures (imGraph) provide an integrated environment for systems level analysis of multivariate data.

BigBang/Horizon is a proteomics data analysis pipeline with focus on the shotgun LC/MSMS workflow.