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RSim: A reference-based normalization method via rank similarity

Fig 6

RSim normalization helps two-sample t-test control false discovery.

Samples are divided into two groups based on the sequencing depth (<10000 belongs to the first group, and >20000 belongs to the second group), and the FDR is shown when the different significance levels are used. In (a), seven normalization methods are compared. In (b), a two-sample t-test equipped with RSim normalization is compared with state-of-art differential abundance tests.

Fig 6

doi: https://doi.org/10.1371/journal.pcbi.1011447.g006