2014 Metabolomic Data Analysis and Visualization Workshop and Tutorials
Recently I had the pleasure of teaching statistical and multivariate data analysis and visualization at the annual Summer Sessions in Metabolomics 2014, organized by the NIH West Coast Metabolomics Center.
Similar to last year, I’ve posted all the content (lectures, labs and software) for any one to follow along with at their own pace. I also plan to release videos for all the lectures and labs including use cases for the freely available data analysis software listed below.
You can check out the introduction lecture to the covered material below.
New additions to the course include lecture and lab on Data normalization and updated and improved software.
Software
Stay tuned for videos of all of the material!
2014 Metabolomics Data Analysis and Visualization Tutorials Dmitry Grapov is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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:
- biochemical
- structural similarity
- mass spectral similarity
- correlation
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!
ASMS 2014
I’ve recently participated in the American Society of Mass Spectrommetry (ASMS) conference and had a great time. I met some great people and have a few new ideas for future projects. Specifically giving a go at using self-organizing maps (SOM) and the R package mcclust for clustering alternatives to hierarchical and k-means methods.
I had the pleasure of speaking at the conference in the Informatics-Metabolomics section, and was also a co-author on a project detailing a multi-metabolomics strategy (primary metabolites, lipids, and oxylipins) for the study of type 1 diabetes in an animal model. Keep an eye out for my full talk in an upcoming post.
Tutorials- Statistical and Multivariate Analysis for Metabolomics
I recently had the pleasure in participating in the 2014 WCMC Statistics for Metabolomics Short Course. The course was hosted by the NIH West Coast Metabolomics Center and focused on statistical and multivariate strategies for metabolomic data analysis. A variety of topics were covered using 8 hands on tutorials which focused on:
- data quality overview
- statistical and power analysis
- clustering
- principal components analysis (PCA)
- partial least squares (O-/PLS/-DA)
- metabolite enrichment analysis
- biochemical and structural similarity network construction
- network mapping
I am happy to have taught the course using all open source software, including: R, and Cytoscape. The data analysis and visualization were done using Shiny-based apps: DeviumWeb and MetaMapR. Check out some of the slides below or download all the class material and try it out for yourself.
2014 WCMC LC-MS Data Processing and Statistics for Metabolomics by Dmitry Grapov is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Special thanks to the developers of Shiny and Radiant by Vincent Nijs.
Introduction to Network Mapping
Network mapping is a high-dimensional data visualization technique which can be applied to virtually any type of data. I recently gave a tutorial on the basics of network mapping where each participants generated a mapped network for their name.
Download the full tutorial at TeachingDemos, and then follow along with the tutorial at your own pace.
Happy network mapping!
Featured Network in Chemical and Engineering News (C&EN)
I am happy to announce the release of MetaMapR (v1.2.0).
New features include:
- An independent module for biological database identifier translations using the Chemical Translation System (CTS)
- a retention time filter for mass spectral connections
- increase in calculation speed
An application of MetaMapR was recently featured in an article in the Nov. 4th 2013 issue of Chemical & Engineering News (C&EN) , 91(44). This tool was used to generate a network of > 1200 metabolites based on enzymatic transformations and structural similarities.
The full article can be found be found here as well as the original image.
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