RNA-Sequencing analysis methods are rapidly evolving, and the tool choice for each step of one common workflow, differential expression analysis, which includes read alignment, expression modeling...
Read More »CirComPara – A Multi-Method Comparative Bioinformatics Pipeline to Detect and Study circRNAs from RNA-seq Data
Circular RNAs (circRNAs) are generated by backsplicing of immature RNA forming covalently closed loops of intron/exon RNA molecules. Pervasiveness, evolutionary conservation, massive and regulated expression, and posttranscriptional regulatory roles of circRNAs in eukaryotes have been...
Read More »Single-cell RNA-seq reveals new types of human blood cells
Dendritic cells (DCs) and monocytes play a central role in pathogen sensing, phagocytosis, and antigen presentation and consist of multiple specialized subtypes. However, their identities and interrelationships are not fully understood. Using unbiased single-cell RNA sequencing (RNA-seq) of ~2400 cells, ...
Read More »There is significant heterogeneity in the performance of RNA-Seq workflows to identify differentially expressed genes
RNA-Seq has supplanted microarrays as the preferred method of transcriptome-wide identification of differentially expressed genes. However, RNA-Seq analysis is still rapidly evolving, with a large number of tools available for each of the three major processing steps: read alignment, expression ...
Read More »Choice of workflow leads to wide variation in gene expression results
RNA-Seq has supplanted microarrays as the preferred method of transcriptome-wide identification of differentially expressed genes. However, RNA-Seq analysis is still rapidly evolving, with a large number of tools available for each of the three major processing steps: read alignment, expression ...
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