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Data analysis workflows part 2 2015

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Dmitry Grapov
Dmitry Grapov

previous: https://github.com/dgrapov/TeachingDemos/blob/master/Demos/Data%20Analysis%20Workflow/report/report.md

Sciences
1  sur  10
Large longitudinal studies may be required to identify small phenotypic and environmental effects http://teddy.epi.usf.edu/TEDDY/ TEDDY: The Environmental Determinants of Type 1 Diabetes in the Young multi-Omic longitudinal study involving > 15,000 samples acquired over 3 yrs Time Time Analytical batch effects can hide smaller biological effects
Data normalization may require a combination of approaches Internal standard (ISTD) based normalization may not fully remove analytical batch effects Analytical replicate-based normalizations can be used to estimate and remove analytical variance Raw Data Normalized Data Samples QCs LOESS
Omic’ data integration strategies Biomarker Insights 2015:Suppl. 4 1-6 DOI: 10.4137/BMI.S29511 Empirical correlation Network based Biochemical pathway
Pathway analysis
Metabolomic network analysis
MetaMapR: Metabolomic network calculation http://dgrapov.github.io/MetaMapR/
Omic’ network analysis http://kwanjeeraw.github.io/grinn/
MappingsNetwork Mapped Network Grapov D.,American Society of Mass Spectrometry Conference (2013, 2014) Network Mapping + =
DeviumWeb: Data analysis and visualization https://github.com/dgrapov/DeviumWeb
Questions? dgrapov@gmail.com More information: https://imdevsoftware.wordpress.com/ Software: https://github.com/dgrapov Hire me: createdatasol@gmail.com

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