Advancing single-cell RNA-seq data analysis through the fusion of multi-layer perceptron and graph neural network
The advancement of single-cell sequencing technology has smoothed the ability to do biological studies at…
Browsing: Statistical Analysis
scIALM – A method for sparse scRNA-seq expression matrix imputation using the Inexact Augmented Lagrange Multiplier with low error
Single-cell RNA sequencing (scRNA-seq) is a high-throughput sequencing technology that quantifies gene expression profiles of…
RedRibbon – A new rank–rank hypergeometric overlap for gene and transcript expression signatures
High-throughput omics technologies have generated a wealth of large protein, gene, and transcript datasets that…
TsImpute – an accurate two-step imputation method for single-cell RNA-seq data
Single-cell RNA sequencing (scRNA-seq) technology has enabled discovering gene expression patterns at single cell resolution.…
Batch-effect correction in single-cell RNA sequencing data using JIVE
In single-cell RNA sequencing (scRNA-seq) data analysis, addressing batch effects – technical artifacts stemming from…
FWP – feature-weight based measurement of cancerous transcriptome using cohort-wide and sample-specific information
Identifying cancerous samples or cells using transcriptomic data is critical for cancer related basic research,…
mitoSplitter – A mitochondrial variants-based method for efficient demultiplexing of pooled single-cell RNA-seq
Single-cell RNA-seq (scRNA-seq) analysis of multiple samples separately can be costly and lead to batch…
iDESC – identifying differential expression in single-cell RNA sequencing data with multiple subjects
Single-cell RNA sequencing (scRNA-seq) technology has enabled assessment of transcriptome-wide changes at single-cell resolution. Due…
STREAK – a supervised cell surface receptor abundance estimation strategy for single cell RNA-sequencing data
The accurate estimation of cell surface receptor abundance for single cell transcriptomics data is important…
Adjusting for gene-specific covariates to improve RNA-seq analysis
A team led by researchers at the Ohio State University have developed a novel positive…