This function computes and visualizes the significance of enriched (over or underrepresented) Phylostrata or Divergence Strata within an input `test.set`

.

1 2 3 4 5 |

`ExpressionSet` |
a standard PhyloExpressionSet or DivergenceExpressionSet object (in case |

`test.set` |
a character vector storing the gene ids for which PS/DS enrichment analyses should be performed. |

`use.only.map` |
a logical value indicating whether instead of a standard |

`measure` |
a character string specifying the measure that should be used to quantify over and under representation of PS/DS. Measures can either be |

`complete.bg` |
a logical value indicating whether the entire background set
of the input |

`legendName` |
a character string specifying whether "PS" or "DS" are used to compute relative expression profiles. |

`over.col` |
color of the overrepresentation bars. |

`under.col` |
color of the underrepresentation bars. |

`epsilon` |
a small value to shift values by epsilon to avoid log(0) computations. |

`cex.legend` |
the |

`cex.asterisk` |
the |

`plot.bars` |
a logical value specifying whether or not bars should be visualized or whether only |

`p.adjust.method` |
correction method to adjust p-values for multiple comparisons (see |

`...` |
default graphics parameters. |

This *Phylostratum* or *Divergence Stratum* enrichment analysis is motivated
by Sestak and Domazet-Loso (2015) who perform *Phylostratum* or *Divergence Stratum* enrichment analyses to correlate organ evolution with the origin of organ specific genes.

In detail this function takes the *Phylostratum* or *Divergence Stratum* distribution of all genes stored in the input `ExpressionSet`

as background set and
the *Phylostratum* or *Divergence Stratum* distribution of the `test.set`

and performes a `fisher.test`

for each *Phylostratum* or *Divergence Stratum* to quantify the statistical significance of over- or underrepresentated *Phylostrata* or *Divergence Strata* within the set of selected `test.set`

genes.

To visualize the odds or log-odds of over or underrepresented genes within the `test.set`

the following procedure is performed:

N_ij denotes the number of genes in group j and deriving from PS i, with

*i = 1, .. , n*and where*j = 1*denotes the background set and*j = 2*denotes the`test.set`

N_i. denotes the total number of genes within PS i

N_.j denotes the total number of genes within group j

N_.. is the total number of genes within all groups j and all PS i

f_ij = N_ij / N_.. and g_ij = f_ij / f_.j denote relative frequencies between groups

f_i. denotes the between group sum of f_ij

The result is the fold-change value (odds) denoted as C = g_i2 / f_i. which is visualized above and below zero.

In case a large number of Phylostrata or Divergence Strata is included in the input
`ExpressionSet`

, p-values returned by `PlotEnrichment`

should be adjusted for
multiple comparisons which can be done by specifying the `p.adjust.method`

argument.

Hajk-Georg Drost

Sestak and Domazet-Loso (2015). Phylostratigraphic Profiles in Zebrafish Uncover Chordate Origins of the Vertebrate Brain. Mol. Biol. Evol. 32(2): 299-312.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | ```
data(PhyloExpressionSetExample)
set.seed(123)
test_set <- sample(PhyloExpressionSetExample[ , 2],10000)
## Examples with complete.bg = TRUE
## Hence: the entire background set of the input ExpressionSet is considered
## when performing Fisher's exact test
# measure: log-foldchange
PlotEnrichment(ExpressionSet = PhyloExpressionSetExample,
test.set = test_set ,
legendName = "PS",
measure = "log-foldchange")
# measure: foldchange
PlotEnrichment(ExpressionSet = PhyloExpressionSetExample,
test.set = test_set ,
legendName = "PS",
measure = "foldchange")
## Examples with complete.bg = FALSE
## Hence: the test.set genes are excluded from the background set before
## Fisher's exact test is performed
# measure: log-foldchange
PlotEnrichment(ExpressionSet = PhyloExpressionSetExample,
test.set = test_set ,
complete.bg = FALSE,
legendName = "PS",
measure = "log-foldchange")
# measure: foldchange
PlotEnrichment(ExpressionSet = PhyloExpressionSetExample,
test.set = test_set ,
complete.bg = FALSE,
legendName = "PS",
measure = "foldchange")
``` |

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