scLENS: data-driven signal detection for unbiased scRNA-seq data analysis
High dimensionality and noise have limited the new biological insights that can be
discovered in scRNA-seq data. While dimensionality reduction tools have been developed …
discovered in scRNA-seq data. While dimensionality reduction tools have been developed …
corral: Single-cell RNA-seq dimension reduction, batch integration, and visualization with correspondence analysis
LL Hsu, AC Culhane - bioRxiv, 2021 - biorxiv.org
Effective dimension reduction is an essential step in analysis of single cell RNA-seq
(scRNAseq) count data, which are high-dimensional, sparse, and noisy. Principal …
(scRNAseq) count data, which are high-dimensional, sparse, and noisy. Principal …
scRNASequest: an ecosystem of scRNA-seq analysis, visualization, and publishing
Background Single-cell RNA sequencing is a state-of-the-art technology to understand gene
expression in complex tissues. With the growing amount of data being generated, the …
expression in complex tissues. With the growing amount of data being generated, the …
Scdrake: a reproducible and scalable pipeline for scRNA-seq data analysis
J Kubovčiak, M Kolář, J Novotný - Bioinformatics Advances, 2023 - academic.oup.com
Motivation While the workflow for primary analysis of single-cell RNA-seq (scRNA-seq) data
is well established, the secondary analysis of the feature-barcode matrix is usually done by …
is well established, the secondary analysis of the feature-barcode matrix is usually done by …
Monet: An open-source Python package for analyzing and integrating scRNA-Seq data using PCA-based latent spaces
F Wagner - bioRxiv, 2020 - biorxiv.org
Single-cell RNA-Seq is a powerful technology that enables the transcriptomic profiling of the
different cell populations that make up complex tissues. However, the noisy and high …
different cell populations that make up complex tissues. However, the noisy and high …
Accuracy, robustness and scalability of dimensionality reduction methods for single-cell RNA-seq analysis
Background Dimensionality reduction is an indispensable analytic component for many
areas of single-cell RNA sequencing (scRNA-seq) data analysis. Proper dimensionality …
areas of single-cell RNA sequencing (scRNA-seq) data analysis. Proper dimensionality …
Tuning parameters of dimensionality reduction methods for single-cell RNA-seq analysis
Background Many computational methods have been developed recently to analyze single-
cell RNA-seq (scRNA-seq) data. Several benchmark studies have compared these methods …
cell RNA-seq (scRNA-seq) data. Several benchmark studies have compared these methods …
Scanorama: integrating large and diverse single-cell transcriptomic datasets
Merging diverse single-cell RNA sequencing (scRNA-seq) data from numerous
experiments, laboratories and technologies can uncover important biological insights …
experiments, laboratories and technologies can uncover important biological insights …
A novel metric reveals previously unrecognized distortion in dimensionality reduction of scRNA-Seq data
SM Cooley, T Hamilton, SD Aragones, JCJ Ray… - Biorxiv, 2019 - biorxiv.org
High-dimensional data are becoming increasingly common in nearly all areas of science.
Developing approaches to analyze these data and understand their meaning is a pressing …
Developing approaches to analyze these data and understand their meaning is a pressing …
scRNA-seq mixology: towards better benchmarking of single cell RNA-seq analysis methods
Single cell RNA sequencing (scRNA-seq) technology has undergone rapid development in
recent years, bringing with it new challenges in data processing and analysis. This has led …
recent years, bringing with it new challenges in data processing and analysis. This has led …