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Updated: Mar 18, 2026

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Published on: November 7, 2025
samExploreR: exploring reproducibility and robustness of RNA-seq results based on SAM files
Alexey Stupnikov1, Shailesh Tripathi2, Ricardo de Matos Simoes1
1Computational Biology and Machine Learning Laboratory, Center for Cancer Research and Cell Biology, School of Medicine, Dentistry and Biomedical Sciences, Faculty of Medicine Health and Life Sciences, Queen's University Belfast, BT9 7AE Belfast, UK.
Motivation:
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 (i) a cost efficient and (ii) an optimal experimental design leading to a compromise, e.g. in the sequencing depth of experiments.
Results:
We 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. We exemplify the usage of samExploreR by studying the influence of the sequencing depth and the annotation on the identification of differentially expressed genes.
Availability And Implementation:
samExploreR is available as an R package from Bioconductor.
Contact:
v@bio-complexity.comSupplementary information: Supplementary data are available at Bioinformatics online.
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