Preprocessing of single cell RNA sequencing data using correlated clustering and projection
Single-cell RNA sequencing (scRNA-seq) is widely used to reveal heterogeneity in cells, which has given…
Browsing: Statistical Analysis
Modelling capture efficiency of single-cell RNA-sequencing data improves inference of transcriptome-wide burst kinetics
Gene expression is characterised by stochastic bursts of transcription that occur at brief and random…
ScInfoVAE – interpretable dimensional reduction of single cell transcription data with variational autoencoders and extended mutual information regularization
Single-cell RNA-sequencing (scRNA-seq) data can serve as a good indicator of cell-to-cell heterogeneity and can…
Celloscope – a probabilistic model for marker-gene-driven cell type deconvolution in spatial transcriptomics data
Spatial transcriptomics maps gene expression across tissues, posing the challenge of determining the spatial arrangement…
Applying a GAN-based classifier to improve transcriptome-based prognostication in breast cancer
Established prognostic tests based on limited numbers of transcripts can identify high-risk breast cancer patients…
Gene expression model inference from snapshot RNA data using Bayesian non-parametrics
Gene expression models, which are key towards understanding cellular regulatory response, underlie observations of single-cell…
DGAN – improved downstream functional analysis of single-cell RNA-sequence data
The dramatic increase in the number of single-cell RNA-sequence (scRNA-seq) investigations is indeed an endorsement…
Correspondence analysis for dimension reduction, batch integration, and visualization of single-cell RNA-seq data
Effective dimension reduction is essential for single cell RNA-seq (scRNAseq) analysis. Principal component analysis (PCA)…
A lineage tree-based hidden Markov model quantifies cellular heterogeneity and plasticity
Individual cells can assume a variety of molecular and phenotypic states and recent studies indicate…
sc-linker – identifying disease-critical cell types and cellular processes by integrating single-cell RNA-sequencing and human genetic
Genome-wide association studies provide a powerful means of identifying loci and genes contributing to disease,…