Tag Archives: power analysis

Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes in RNA-seq data. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and ...

Simulations are essential to find the best compromise between statistical power and cost effectiveness, but also help with the interpretation of conducted RNA-seq experiments. For example, researchers often wonder why their results differ from previous studies, powsim helps here by ...

Single-cell RNA sequencing (scRNA-seq) has become an established and powerful method to investigate transcriptomic cell-to-cell variation, thereby revealing new cell types and providing insights into developmental processes and transcriptional stochasticity. A key question is how the variety of available protocols ...

RNA-Sequencing (RNA-Seq) has become a routine technology for investigating gene expression differences in comparative transcriptomic studies. Differential expression (DE) analysis of the isoforms of genes is just emerging now that expression (read counts) can be estimated with higher accuracy at ...

As RNA-seq rapidly develops and costs continually decrease, the quantity and frequency of samples being sequenced will grow exponentially. With proteomic investigations becoming more multivariate and quantitative, determining a study’s optimal sample size is now a vital step in experimental ...

High-throughput single cell RNA sequencing (scRNA-seq) has become an established and powerful method to investigate transcriptomic cell-to-cell variation, and has revealed new cell types, and new insights into developmental process and stochasticity in gene expression. There are now several published ...

RNA-Sequencing (RNA-seq) experiments have been popularly applied to transcriptome studies in recent years. Such experiments are still relatively costly. As a result, RNA-seq experiments often employ a small number of replicates. Power analysis and sample size calculation are challenging in ...

Reference is regularly made to the power of new genomic sequencing approaches. Using powerful technology, however, is not the same as having the necessary power to address a research question with statistical robustness. In the rush to adopt new and ...

Next generation sequencing methods, such as RNA-seq, have permitted the exploration of gene expression in a range of organisms which have been studied in ecological contexts but lack a sequenced genome. However, the efficacy and accuracy of RNA-seq annotation methods ...

It is crucial for researchers to optimize RNA-seq experimental designs for differential expression detection. Currently, the field lacks general methods to estimate power and sample size for RNA-Seq in complex experimental designs, under the assumption of the negative binomial distribution. ...