Current best practices in single‐cell RNA‐seq analysis: a tutorial
MD Luecken, FJ Theis - Molecular systems biology, 2019 - embopress.org
Single‐cell RNA‐seq has enabled gene expression to be studied at an unprecedented
resolution. The promise of this technology is attracting a growing user base for single‐cell …
resolution. The promise of this technology is attracting a growing user base for single‐cell …
A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications
RNA sequencing (RNA-seq) is a genomic approach for the detection and quantitative
analysis of messenger RNA molecules in a biological sample and is useful for studying …
analysis of messenger RNA molecules in a biological sample and is useful for studying …
A comparison of single-cell trajectory inference methods
Trajectory inference approaches analyze genome-wide omics data from thousands of single
cells and computationally infer the order of these cells along developmental trajectories …
cells and computationally infer the order of these cells along developmental trajectories …
Single-cell RNA-seq denoising using a deep count autoencoder
Single-cell RNA sequencing (scRNA-seq) has enabled researchers to study gene
expression at a cellular resolution. However, noise due to amplification and dropout may …
expression at a cellular resolution. However, noise due to amplification and dropout may …
DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data
Single-cell RNA sequencing (scRNA-seq) offers new opportunities to study gene expression
of tens of thousands of single cells simultaneously. We present DeepImpute, a deep neural …
of tens of thousands of single cells simultaneously. We present DeepImpute, a deep neural …
Next-generation computational tools for interrogating cancer immunity
The remarkable success of cancer therapies with immune checkpoint blockers is
revolutionizing oncology and has sparked intensive basic and translational research into the …
revolutionizing oncology and has sparked intensive basic and translational research into the …
Benchmarking principal component analysis for large-scale single-cell RNA-sequencing
K Tsuyuzaki, H Sato, K Sato, I Nikaido - Genome biology, 2020 - Springer
Background Principal component analysis (PCA) is an essential method for analyzing single-
cell RNA-seq (scRNA-seq) datasets, but for large-scale scRNA-seq datasets, computation …
cell RNA-seq (scRNA-seq) datasets, but for large-scale scRNA-seq datasets, computation …
Evaluation of cell type annotation R packages on single-cell RNA-seq data
Annotating cell types is a critical step in single-cell RNA sequencing (scRNA-seq) data
analysis. Some supervised or semi-supervised classification methods have recently …
analysis. Some supervised or semi-supervised classification methods have recently …
Single cell transcriptome research in human placenta
H Li, Q Huang, Y Liu, LX Garmire - Reproduction, 2020 - rep.bioscientifica.com
Human placenta is a complex and heterogeneous organ interfacing between the mother
and the fetus that supports fetal development. Alterations to placental structural components …
and the fetus that supports fetal development. Alterations to placental structural components …
Reproducibility of methods to detect differentially expressed genes from single-cell RNA sequencing
Detection of differentially expressed genes is a common task in single-cell RNA-seq (scRNA-
seq) studies. Various methods based on both bulk-cell and single-cell approaches are in …
seq) studies. Various methods based on both bulk-cell and single-cell approaches are in …