Adapted tensor decomposition and PCA based unsupervised feature extraction select more biologically reasonable differentially expressed genes than conventional methods
Abstract Tensor decomposition- and principal component analysis-based unsupervised feature extraction were proposed almost 5 and 10 years ago, respectively; although these methods have been successfully applied to a wide range of genome analyses, including drug repositioning, biomarker identificatio...
Main Authors: | Y-h. Taguchi, Turki Turki |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2022-10-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-022-21474-z |
Similar Items
-
Tensor-Decomposition-Based Unsupervised Feature Extraction Applied to Prostate Cancer Multiomics Data
by: Y-h. Taguchi, et al.
Published: (2020-12-01) -
Tensor-Decomposition-Based Unsupervised Feature Extraction in Single-Cell Multiomics Data Analysis
by: Y-h. Taguchi, et al.
Published: (2021-09-01) -
Tensor Decomposition-Based Unsupervised Feature Extraction Applied to Single-Cell Gene Expression Analysis
by: Y-h. Taguchi, et al.
Published: (2019-09-01) -
Application note: TDbasedUFE and TDbasedUFEadv: bioconductor packages to perform tensor decomposition based unsupervised feature extraction
by: Y-h. Taguchi, et al.
Published: (2023-09-01) -
Unsupervised tensor decomposition-based method to extract candidate transcription factors as histone modification bookmarks in post-mitotic transcriptional reactivation.
by: Y-H Taguchi, et al.
Published: (2021-01-01)