Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data
Single-cell RNA sequencing (scRNA-seq) is a popular and powerful technology that allows
you to profile the whole transcriptome of a large number of individual cells. However, the …
you to profile the whole transcriptome of a large number of individual cells. However, the …
Challenges in unsupervised clustering of single-cell RNA-seq data
Single-cell RNA sequencing (scRNA-seq) allows researchers to collect large catalogues
detailing the transcriptomes of individual cells. Unsupervised clustering is of central …
detailing the transcriptomes of individual cells. Unsupervised clustering is of central …
Giotto: a toolbox for integrative analysis and visualization of spatial expression data
Spatial transcriptomic and proteomic technologies have provided new opportunities to
investigate cells in their native microenvironment. Here we present Giotto, a comprehensive …
investigate cells in their native microenvironment. Here we present Giotto, a comprehensive …
SCENIC: single-cell regulatory network inference and clustering
S Aibar, CB González-Blas, T Moerman… - Nature …, 2017 - nature.com
We present SCENIC, a computational method for simultaneous gene regulatory network
reconstruction and cell-state identification from single-cell RNA-seq data (http://scenic …
reconstruction and cell-state identification from single-cell RNA-seq data (http://scenic …
SAVER: gene expression recovery for single-cell RNA sequencing
In single-cell RNA sequencing (scRNA-seq) studies, only a small fraction of the transcripts
present in each cell are sequenced. This leads to unreliable quantification of genes with low …
present in each cell are sequenced. This leads to unreliable quantification of genes with low …
Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance
SM Shaffer, MC Dunagin, SR Torborg, EA Torre… - Nature, 2017 - nature.com
Therapies that target signalling molecules that are mutated in cancers can often have
substantial short-term effects, but the emergence of resistant cancer cells is a major barrier …
substantial short-term effects, but the emergence of resistant cancer cells is a major barrier …
Tutorial: guidelines for annotating single-cell transcriptomic maps using automated and manual methods
Single-cell transcriptomics can profile thousands of cells in a single experiment and identify
novel cell types, states and dynamics in a wide variety of tissues and organisms. Standard …
novel cell types, states and dynamics in a wide variety of tissues and organisms. Standard …
SC3: consensus clustering of single-cell RNA-seq data
Single-cell RNA-seq enables the quantitative characterization of cell types based on global
transcriptome profiles. We present single-cell consensus clustering (SC3), a user-friendly …
transcriptome profiles. We present single-cell consensus clustering (SC3), a user-friendly …
Assessment of computational methods for the analysis of single-cell ATAC-seq data
Background Recent innovations in single-cell Assay for Transposase Accessible Chromatin
using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands …
using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands …
Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic data
Identification of cell populations often relies on manual annotation of cell clusters using
established marker genes. However, the selection of marker genes is a time-consuming …
established marker genes. However, the selection of marker genes is a time-consuming …