OmicsPLS is an R package to integrate two (omics) datasets. There were two major limitations until now.
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OmicsPLS analysis of mRNA and miRNA data
This post will be about using OmicsPLS to integrate two real datasets: transcriptomics and miRNA-omics from cancer patients These data are available freely on the JIVE website. They have been previously analyzed by JIVE (of course) with nice results, see the article associated with DOI:10.1214/12-AOAS597.
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A gentle introduction to OmicsPLS III
An alternative to cross-validation with OmicsPLS
In the previous post, we discussed an alternative to cross-validation to select the number of components to retain. The scree plot can be a good visual alternative if data exploration is more important than prediction. In this post, we will go through the interpretation of the scree plot and how...
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A gentle introduction to OmicsPLS II
An alternative to cross-validation with OmicsPLS
In the previous post, we briefly went throug the cross-validation
function in OmicsPLS and how to choose the number of components. This
post is meant as an extension, in which we will look at an alternative
approach for the number of components in OmicsPLS.
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A gentle introduction to OmicsPLS
How to do cross-validation with OmicsPLS
Implementing software for omics data integration can be challenging. The statistical theory is often complex, and the code needs to run fast. (To make things worse, there are many definitions and solutions for omics data integration!) Our data integration approach in OmicsPLS has statistical theory ‘under the hood’ (see the...
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