Single cell RNA-sequencing (scRNA-seq) technology has undergone rapid development in recent years, leading to an explosion in the number of tailored data analysis methods. However, the current lack of gold-standard benchmark datasets makes it difficult...
Read More »RNA-seq mixology – designing realistic control experiments to compare protocols and analysis methods
Carefully designed control experiments provide a gold standard for benchmarking new platforms, protocols and pipelines in genomics research. RNA profiling control studies frequently use the mixture design, which takes two distinct samples and combines them in known proportions to induce ...
Read More »Modelling sample and observational level variability improves power in RNA-seq analyses
Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to ...
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