Multivariate Data Analysis and Visualization Through Network Mapping
Recently I had the pleasure of speaking about one of my favorite topics, Network Mapping. This is a continuation of a general theme I’ve previously discussed and involves the merger of statistical and multivariate data analysis results with a network.
Over the past year I’ve been working on two major tools, DeviumWeb and MetaMapR, which aid the process of biological data (metabolomic) network mapping.
DeviumWeb– is a shiny based GUI written in R which is useful for:
- data manipulation, transformation and visualization
- statistical analysis (hypothesis testing, FDR, power analysis, correlations, etc)
- clustering (heiarchical, TODO: k-means, SOM, distribution)
- principal components analysis (PCA)
- orthogonal partial least squares multivariate modeling (O-/PLS/-DA)
MetaMapR– is also a shiny based GUI written in R which is useful for calculation and visualization of various networks including:
- structural similarity
- mass spectral similarity
Both of theses projects are under development, and my ultimate goal is to design a one-stop-shop ecosystem for network mapping.
In addition to network mapping,the video above and presentation below also discuss normalization schemes for longitudinal data and genomic, proteomic and metabolomic functional analysis both on a pathway and global level.
As always happy network mapping!
This entry was posted on June 27, 2014 by dgrapov. It was filed under Uncategorized and was tagged with biochemical network, chemical similarity network, correlation network, Cytoscape, data analysis, data visualization, DeviumWeb, ggplot2, metabolomics, MetaMapR, multivariate, network mapping, O-PLS, R, r-bloggers, shiny, statistical analysis.