Stability of methods for differential expression analysis of RNA-seq data.

ABSTRACT:

Background

As RNA-seq becomes the assay of choice for measuring gene expression levels, differential expression analysis has received extensive attentions of researchers. To date, for the evaluation of DE methods, most attention has been paid on validity. Yet another important aspect of DE methods, stability, is overlooked and has not been studied to the best of our knowledge.

Results

In this study, we empirically show the need of assessing stability of DE methods and propose a stability metric, called Area Under the Correlation curve (AUCOR), that generates the perturbed datasets by a mixture distribution and combines the information of similarities between sets of selected features from these perturbed datasets and the original dataset.

Conclusion

Empirical results

SUBMITTER: Lin B 

PROVIDER: S-EPMC6330476 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature