Neighboring cell types influence single-cell gene expression variability
Researchers from the University of Tsukuba have designed a statistical framework that identifies regulation of…
Browsing: Statistical Analysis
CellRegMap – a statistical framework for mapping context-specific regulatory variants using scRNA-seq
Single-cell RNA sequencing (scRNA-seq) enables characterizing the cellular heterogeneity in human tissues. Recent technological advances…
Significance analysis for clustering with single-cell RNA-sequencing data
Unsupervised clustering of single-cell RNA-sequencing data enables the identification and discovery of distinct cell populations.…
Current statistical approaches and outstanding challenges to differential expression analysis of single-cell RNA-seq data
With the advent of single-cell RNA-sequencing (scRNA-seq), it is possible to measure the expression dynamics…
Batch effect detection and correction in RNA-seq data using machine-learning-based automated assessment of quality
The constant evolving and development of next-generation sequencing techniques lead to high throughput data composed…
scDLC – a deep learning framework to classify large sample single-cell RNA-seq data
Using single-cell RNA sequencing (scRNA-seq) data to diagnose disease is an effective technique in medical…
scISR – a novel method for single-cell data imputation using subspace regression
Recent advances in biochemistry and single-cell RNA sequencing (scRNA-seq) have allowed us to monitor the…
ResPAN – a powerful batch correction model for scRNA-seq data through residual adversarial networks
With the advancement of technology, we can generate and access large-scale, high dimensional and diverse…
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…