## Table 3 |
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Summary of the parameters used to generate the synthetic data sets |
|||||

Sim. study |
|{g;ϕ_{g} = 0}| |
‘Single’ outlier fraction |
‘Random’ outlier fraction |
||

0 | 0 | 0 | 0 | 0 | |

1,250 | 0 | 0 | 0 | 0 | |

625 | 625 | 0 | 0 | 0 | |

4,000 | 0 | 0 | 0 | 0 | |

2,000 | 2,000 | 0 | 0 | 0 | |

0 | 0 | 6,250 | 0 | 0 | |

625 | 625 | 6,250 | 0 | 0 | |

0 | 0 | 0 | 10% | 0 | |

625 | 625 | 0 | 10% | 0 | |

0 | 0 | 0 | 0 | 5% | |

625 | 625 | 0 | 0 | 5% |

In all synthetic data sets, the observations were distributed between two conditions
(denoted S_{1} and S_{2}), with the same number of observations (2, 5 or 10) in each condition. We let and denote, respectively, the number of genes that were up- and downregulated in condition
S_{2} compared to S_{1}. The number of genes whose counts were drawn from a Poisson distribution (i.e., with
the dispersion parameter equal to zero) is given by |{*g*; *ϕ*_{g} = 0}|. The ‘single’ outlier fraction denotes the fraction of the genes for which
we selected a single sample and multiplied the corresponding count with a factor between
5 and 10. The ‘random’ outlier fraction denotes the fraction of counts that were selected
randomly (among all counts) and multiplied with a factor between 5 and 10. The notation
for the simulation studies (leftmost column) summarizes the type of simulation (*B* - ‘baseline’, *P* - ‘Poisson’, *S* - ‘single outlier’, *R* - ‘random outlier‘), the number of DE genes that are upregulated in S_{2} (i.e., , in the superscript) and the number of DE genes that are downregulated in S_{2} (i.e., , in the subscript).

Soneson and Delorenzi

Soneson and Delorenzi *BMC Bioinformatics* 2013 **14**:91 doi:10.1186/1471-2105-14-91