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…
Browsing: Expression and Quantification
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…
nf-rnaSeqCount – a Nextflow pipeline for obtaining raw read counts from RNA-seq data
The rate of raw sequence production through Next-Generation Sequencing (NGS) has been growing exponentially due…