Explanation of TDbasedUFEadv (original) (raw)

Contents

• 1 Introduction
  • 1.1 Motivations
  • 1.2 What differs from related packages.
• 2 Integrated analysis of two omics data sets
  • 2.1 When features are shared.
    * 2.1.1 Full tensor
    * 2.1.2 Matrix generated by partial summation
  • 2.2 When samples are shared.
    * 2.2.1 Full tensor
    * 2.2.2 Matrix generated from partial summation
• 3 Integrated analysis using projection
  • 3.1 When samples are shared.
  • 3.2 When features are shared.

#library(TDbasedUFEadv)

Introduction

Since TDbasedUFEadv is an advanced package from TDbasedUFE (Taguchi 2023), please master the contents in TDbasedUFE prior to the trial of this package.

Motivations

Since the publication of the book (Taguchi 2020) describing the methodology, I have published numerous papers using this method. In spite of that, very limited number of researcher used this method, possibly because of unfamiliarity with the mathematical concepts used in this methodology, tensors. Thus I decided to develop the packages by which users can use the methods without detailed knowledge about the tensor.

Integrated analysis of two omics data sets

Integrated analysis using projection

Here we would like to propose an alternative strategy to integrate multiple tensors using projection with SVD.