Principal component analysis

M Greenacre, PJF Groenen, T Hastie… - Nature Reviews …, 2022 - nature.com
Principal component analysis is a versatile statistical method for reducing a cases-by-
variables data table to its essential features, called principal components. Principal …

Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications

M Su, T Pan, QZ Chen, WW Zhou, Y Gong, G Xu… - Military Medical …, 2022 - Springer
The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has
advanced our understanding of the pathogenesis of disease and provided valuable insights …

Biologically informed deep learning to query gene programs in single-cell atlases

M Lotfollahi, S Rybakov, K Hrovatin… - Nature Cell …, 2023 - nature.com
The increasing availability of large-scale single-cell atlases has enabled the detailed
description of cell states. In parallel, advances in deep learning allow rapid analysis of newly …

ATTED-II v11: a plant gene coexpression database using a sample balancing technique by subagging of principal components

T Obayashi, H Hibara, Y Kagaya, Y Aoki… - Plant and Cell …, 2022 - academic.oup.com
Abstract ATTED-II (https://atted. jp) is a gene coexpression database for nine plant species
based on publicly available RNAseq and microarray data. One of the challenges in …

Analysis and visualization of spatial transcriptomic data

B Liu, Y Li, L Zhang - Frontiers in Genetics, 2022 - frontiersin.org
Human and animal tissues consist of heterogeneous cell types that organize and interact in
highly structured manners. Bulk and single-cell sequencing technologies remove cells from …

pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single cell RNA-seq preprocessing tools

PL Germain, A Sonrel, MD Robinson - Genome biology, 2020 - Springer
Abstract We present pipeComp (https://github. com/plger/pipeComp), a flexible R framework
for pipeline comparison handling interactions between analysis steps and relying on multi …

Single-cell and single-nuclei RNA sequencing as powerful tools to decipher cellular heterogeneity and dysregulation in neurodegenerative diseases

R Cuevas-Diaz Duran, JC González-Orozco… - Frontiers in Cell and …, 2022 - frontiersin.org
Neurodegenerative diseases affect millions of people worldwide and there are currently no
cures. Two types of common neurodegenerative diseases are Alzheimer's (AD) and …

Deciphering the biology of circulating tumor cells through single-cell RNA sequencing: implications for precision medicine in cancer

S Orrapin, P Thongkumkoon, S Udomruk… - International Journal of …, 2023 - mdpi.com
Circulating tumor cells (CTCs) hold unique biological characteristics that directly involve
them in hematogenous dissemination. Studying CTCs systematically is technically …

Unsupervised pattern identification in spatial gene expression atlas reveals mouse brain regions beyond established ontology

R Cahill, Y Wang, RP Xian, AJ Lee, H Zeng… - Proceedings of the …, 2024 - pnas.org
The rapid growth of large-scale spatial gene expression data demands efficient and reliable
computational tools to extract major trends of gene expression in their native spatial context …

Fast and accurate out-of-core PCA framework for large scale biobank data

Z Li, J Meisner, A Albrechtsen - Genome Research, 2023 - genome.cshlp.org
Principal component analysis (PCA) is widely used in statistics, machine learning, and
genomics for dimensionality reduction and uncovering low-dimensional latent structure. To …