Subpopulation identification, usually via some form of unsupervised clustering, is a fundamental step in the analysis of many single-cell RNA-seq data sets. This has motivated the development and application of a broad range of clustering methods, based on various..
Read More »New RNA-Seq Workflows
CSAMA 2016: Statistical Data Analysis for Genome-Scale Biology July 10-15, 2016 Bressanone-Brixen, Italy New RNA-seq Workflows Charlotte Soneson – University of Zurich
Read More »Don’t bother with transcript level analysis
High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be ...
Read More »Isoform prefiltering improves performance of count-based methods for analysis of differential transcript usage
RNA-seq has been a boon to the quantitative analysis of transcriptomes. A notable application is the detection of changes in transcript usage between experimental conditions. For example, discovery of pathological alternative splicing may allow the development of new treatments or ...
Read More »Differential transcript usage from RNA-seq data – isoform pre-filtering improves performance of count-based methods
Large-scale sequencing of cDNA (RNA-seq) has been a boon to the quantitative analysis of transcriptomes. A notable application is the detection of changes in transcript usage between experimental conditions. For example, discovery of pathological alternative splicing may allow the development ...
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