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  "Description": "Differential expression analysis is commonly used to study\ndiverse biological datasets. The reproducibility-optimized test\nstatistic (ROTS) (Elo et al., 2008,\n<doi:10.1109/tcbb.2007.1078>) uses a modified t-statistic to\nprioritise features that differ between two or more groups.\nHowever, the ROTS Bioconductor implementation (Suomi et al.,\n2017, <doi:10.1371/journal.pcbi.1005562>) did not accommodate\ntechnical or biological covariates. LimROTS (Anwar et al.,\n2025, <doi:10.1093/bioinformatics/btaf570>) addressed this\nlimitation by combining a reproducibility-optimized test\nstatistic with the limma empirical Bayes approach (Ritchie et\nal., 2015, <doi:10.1093/nar/gkv007>). This enables the analysis\nof more complex experimental designs and the incorporation of\ncovariates.",
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