We present a large-scale benchmark of 72 confounder-aware differential abundance analysis (DAA) strategies, assembled from six input schemes (five normalization approaches plus raw counts) and 14 statistical models.
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We benchmark DAA strategies under complex confounding and batch effects, delivering robust pipelines and best practices for identifying differential microbes.
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zhuxinyue1998/xConDA_benchmark
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We benchmark DAA strategies under complex confounding and batch effects, delivering robust pipelines and best practices for identifying differential microbes.
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