Single-cell RNA-sequencing (scRNA-seq) is a recent high-throughput sequencing technique for studying gene expressions at the cell level. Differential...
Read More »IDEAS – individual level differential expression analysis for single-cell RNA-seq data
A team led by researchers at the Fred Hutchison Cancer Research Center considers an increasingly popular study design where single-cell RNA-seq...
Read More »MGcount – a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts
Total-RNA sequencing (total-RNA-seq) allows the simultaneous study of both the coding and the non-coding transcriptome. Yet, computational pipelines...
Read More »Dashboard-style interactive plots for RNA-seq analysis are R Markdown ready with Glimma 2.0
Glimma 1.0 introduced intuitive, point-and-click interactive graphics for differential gene expression analysis. Researchers at the Walter and Eliza Hall Institute of Medical Research present a major update to Glimma that brings improved interactivity and...
Read More »A technique to discover gene expression spatial patterns from single-cell RNA-Seq data
Researchers at the University of Alabama at Birmingham have developed Polar Gini Curve, a method for characterizing cluster markers by...
Read More »LocCSN – constructing local cell-specific networks from single-cell data
Gene coexpression networks yield critical insights into biological processes, and single-cell RNA sequencing provides an opportunity to target...
Read More »CIDER – an interpretable meta-clustering framework for single-cell RNA-seq data integration and evaluation
Clustering of joint single-cell RNA-Seq (scRNA-Seq) data is often challenged by confounding factors, such as batch effects and biologically relevant variability. Existing batch effect removal methods typically...
Read More »Replicate sequencing libraries are important for quantification of allelic imbalance
A sensitive approach to quantitative analysis of transcriptional regulation in diploid organisms is analysis of allelic imbalance (AI) in RNA sequencing..
Read More »Deconvolution of expression for nascent RNA sequencing data highlights pre-RNA isoform diversity in human cells
Quantification of isoform abundance has been extensively studied at the mature-RNA level using RNA-seq but not at the level of precursor RNAs using nascent RNA sequencing. Researchers from Cold...
Read More »GapClust – a light-weight approach distinguishing rare cells from voluminous single cell expression profiles
Single cell RNA sequencing (scRNA-seq) is a powerful tool in detailing the cellular landscape within complex tissues. Large-scale single cell transcriptomics provide both opportunities and challenges...
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