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…
Browsing: Expression and Quantification
OUTRIDER – a statistical method for detecting aberrantly expressed genes in RNA sequencing data
RNA sequencing (RNA-seq) is gaining popularity as a complementary assay to genome sequencing for precisely…
ParslRNA-Seq – an efficient and scalable RNAseq analysis workflow for studies of differentiated gene expression
RNA sequencing has become an increasingly affordable way to profile gene expression analyses. Researchers from…
Single-molecule counting method for digital quantification of SARS-CoV-2 RNA
Digital counting individual nucleic acid molecule is of great significance for fundamental biological research and…
SPECK – an unsupervised learning approach for cell surface receptor abundance estimation for single cell RNA-sequencing data
The rapid development of single cell transcriptomics has revolutionized the study of complex tissues. Single…
Neighboring cell types influence single-cell gene expression variability
Researchers from the University of Tsukuba have designed a statistical framework that identifies regulation of…
Kyoto scientists use mathematics to extract clear signals from single-cell RNA sequencing data
Since scientists first mapped the complete human genome, attention has now turned to the question…
NBBt-test – a versatile method for differential analysis of multiple types of RNA-seq data
Rapid development of transcriptome sequencing technologies has resulted in a data revolution and emergence of…
scCAN – single-cell clustering using autoencoder and network fusion
Unsupervised clustering of single-cell RNA sequencing data (scRNA-seq) is important because it allows us to…
MURP – a downsampling method that enables robust clustering and integration of single-cell transcriptome data
The random noises, sampling biases, and batch effects often confound true biological variations in single-cell…