Data from RNA-seq experiments provide us with many new possibilities to gain insights into biological and disease mechanisms of cellular functioning. However, the reproducibility and robustness of RNA-seq data analysis results is often unclear. This is in part attributed to the two counter acting goals of (a) a cost efficient and (b) an optimal experimental design leading to a compromise, e.g., in the sequencing depth of experiments.
Queen’s University Belfast researchers introduce an R package called samExploreR that allows the subsampling (m out of n bootstraping) of short-reads based on SAM files facilitating the investigation of sequencing depth related questions for the experimental design. Overall, this provides a systematic way for exploring the reproducibility and robustness of general RNA-seq studies. The researchers exemplify the usage of samExploreR by studying the influence of the sequencing depth and the annotation on the identification of differentially expressed genes.
Results from samExploreR
(A) Number of DE genes for three annotations and (B) their pairwise intersections of common DE genes. The Venn diagram is for intersections at f = 0:7 (vertical dashed line) whereas r is the number of used f values.
Availability – samExploreR is available as an R package from Bioconductor (after acceptance of the paper, download link: http://www.bio-complexity.com/samExploreR_1.0.0.tar.gz).
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