Article

Two-stage Linked Component Analysis for Joint Decomposition of Multiple Biologically Related Data Sets

2021-03-22

Abstract excerpt

<h4> S ummary </h4> Integrative analysis of multiple data sets has the potential of fully leveraging the vast amount of high throughput biological data being generated. In particular such analysis will be powerful in making inference from publicly available collections of genetic, transcriptomic and epigenetic data sets which are designed to study shared biological processes, but which vary in their target meas...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: cb9c7adb-010c-5dc9-be55-122615b9e3ab
DOI: 10.1101/2021.03.22.435728

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Two-stage Linked Component Analysis for Joint Decomposition of Multiple Biologically Related Data SetsDOI 10.1101/2021.03.22.435728Read

Organisation of gene programs revealed by unsupervised analysis of diverse gene-trait associationsSemantic proximity Read

Statistical Integration of Two Omics Datasets Using GO2PLSSemantic proximity Read

Organization of gene programs revealed by unsupervised analysis of diverse gene-trait associations.Semantic proximity Read

Exploring transcriptomic and genomic latent variable correction approaches in differential expression analysisSemantic proximity Read

Integrative, multi-omics, analysis of blood samples improves model predictions: applications to cancerSemantic proximity Read

Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets.Semantic proximity Read

Mapping gene expression quantitative trait loci by singular value decomposition and independent component analysis.Semantic proximity Read

Coupled Mixed Model for Joint Genetic Analysis of Complex Disorders with Two Independently Collected Data SetsSemantic proximity Read

Principal component analysis based methods in bioinformatics studies.Semantic proximity Read

AC-PCA: simultaneous dimension reduction and adjustment for confounding variationSemantic proximity Read

Statistical significance of variables driving systematic variation in high-dimensional data.Semantic proximity Read

Subpopulation identification for single-cell RNA-sequencing data using functional data analysisSemantic proximity Read