RNA-Seq Blog Transcriptome Research & Industry News
Single-cell RNA-sequencing (scRNA-seq) has brought the study of the transcriptome to higher resolution and makes it possible for scientists to provide...
Read More »SC2P – two-phase differential expression analysis for single cell RNA-seq
clusterExperiment and RSEC – A Bioconductor package and framework for clustering of single-cell and other large gene expression datasets
Clustering of genes and/or samples is a common task in gene expression analysis. The goals in clustering can vary, but an important scenario is that of...
Read More »The impact of similarity metrics on single-cell RNA-seq data clustering
Advances in high-throughput sequencing on single-cell gene expressions [single-cell RNA sequencing (scRNA-seq)] have enabled transcriptome profiling on individual cells from complex samples. A common goal in scRNA-seq data...
Read More »CellBIC: bimodality-based top-down clustering of single-cell RNA sequencing data reveals hierarchical structure of the cell type
Single-cell RNA sequencing (scRNA-seq) is a powerful tool to study heterogeneity and dynamic changes in cell populations. Clustering scRNA-seq is essential in identifying new cell types and studying their characteristics. University of Pennsylvania...
Read More »Using supervised learning methods for gene selection in RNA-Seq case-control studies
Whole transcriptome studies typically yield large amounts of data, with expression values for all genes or transcripts of the genome. The search for genes...
Read More »Interpretation of differential gene expression results of RNA-seq data
Differential gene expression (DGE) analysis is one of the most common applications of RNA-sequencing (RNA-seq) data. This process allows for the elucidation of differentially expressed genes across two or more conditions and is widely used in many...
Read More »ScISOr-Seq – single-cell isoform RNA sequencing
Full-length isoform sequencing has advanced our knowledge of isoform biology. However, apart from applying full-length isoform sequencing to very few single cells, isoform sequencing has been limited...
Read More »dropEst – pipeline for accurate estimation of molecular counts in droplet-based single-cell RNA-seq experiments
Recent single-cell RNA-seq protocols based on droplet microfluidics use massively multiplexed barcoding to enable simultaneous measurements of transcriptomes for thousands of individual cells. The increasing complexity of such data creates challenges for subsequent computational processing...
Read More »Potential pitfalls in analyzing and quantifying lowly-expressed genes and small RNAs with alignment-free pipelines
Alignment-free RNA quantification tools have significantly increased the speed of RNA-seq analysis. However, it is unclear whether these state-of-the-art RNA-seq analysis pipelines can quantify...
Read More »SAVER – gene expression recovery for single-cell RNA sequencing
In single-cell RNA sequencing (scRNA-seq) studies, only a small fraction of the transcripts present in each cell are sequenced. This leads to unreliable...
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