Description Usage Arguments Value Examples

This function performs multivariate gene set enrichment analysis.

1 2 3 4 5 6 7 8 | ```
mitch_calc(
x,
genesets,
minsetsize = 10,
cores = detectCores() - 1,
resrows = 50,
priority = NULL
)
``` |

`x` |
a multicolumn numerical table with each column containing differential expression scores for a contrast. Rownames must match genesets. |

`genesets` |
lists of genes imported by the gmt_imprt function or similar. |

`minsetsize` |
the minimum number of genes required in a set for it to be included in the statistical analysis. Default is 10. |

`cores` |
the number of parallel threads for computation. Defaults to the number of cores present minus 1. |

`resrows` |
an integer value representing the number of top genesets for which a detailed report is to be generated. Default is 50. |

`priority` |
the prioritisation metric used to selecting top gene sets. Valid options are 'significance', 'effect' and 'SD'. |

mitch res object with the following parts: $input_profile: the supplied input differential profile $input_genesets: the supplied input gene sets $ranked_profile: the differential profile after ranking $enrichment_result: the table of MANOVA/ANOVA enrichment results for each gene set $analysis_metrics: several metrics that are important to the interpretation of the results $detailed_sets: a list of dataframes containing ranks of members of prioritised gene sets.

1 2 3 4 5 | ```
# Example using mitch to calculate multivariate enrichments and
# prioritise based on effect size
data(myImportedData,genesetsExample)
resExample<-mitch_calc(myImportedData,genesetsExample,priority='effect',
minsetsize=5,cores=2)
``` |

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