vi_comparison: vi_comparison
In ScialdoneLab/MitoHEAR: Quantification of Mitochondrial DNA Heteroplasmy
View source: R/lineage_tracing.R
vi_comparison R Documentation
vi_comparison
Description
We compute the variation of information (VI) between the partition provided
by new_classification and old_classification. The VI between a
random partitions (obtained with re-shuffle from original labels in
old_classification) and old_classification is also computed. A
distribution of VI values from random partitions is built. Finally, from the
comparison with this distribution, an empirical p value is given to the VI
of the unsupervised cluster analysis.
Usage
vi_comparison(old_classification, new_classification, number_iter)
Arguments
old_classification
Character vector. First column of the dataframe
returned by function clustering_angular_distance (first element of the
output).
new_classification
Character vector.Second column of the dataframe
returned by function clustering_angular_distance (first element of the
output).
number_iter
Integer value. Specify how many random partition are
generated (starting from re-shuffle of labels in old_classification).
Value
Empirical p value.
Author(s)
Gabriele Lubatti gabriele.lubatti@helmholtz-muenchen.de
See Also
https://www.rdocumentation.org/packages/mcclust/versions/1.0/topics/vi.dist
ScialdoneLab/MitoHEAR documentation built on June 11, 2022, 7:18 a.m.
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View source: R/lineage_tracing.R
| vi_comparison | R Documentation |
vi_comparison
Description
We compute the variation of information (VI) between the partition provided by new_classification and old_classification. The VI between a random partitions (obtained with re-shuffle from original labels in old_classification) and old_classification is also computed. A distribution of VI values from random partitions is built. Finally, from the comparison with this distribution, an empirical p value is given to the VI of the unsupervised cluster analysis.
Usage
vi_comparison(old_classification, new_classification, number_iter)
Arguments
old_classification |
Character vector. First column of the dataframe returned by function clustering_angular_distance (first element of the output). |
new_classification |
Character vector.Second column of the dataframe returned by function clustering_angular_distance (first element of the output). |
number_iter |
Integer value. Specify how many random partition are generated (starting from re-shuffle of labels in old_classification). |
Value
Empirical p value.
Author(s)
Gabriele Lubatti gabriele.lubatti@helmholtz-muenchen.de
See Also
https://www.rdocumentation.org/packages/mcclust/versions/1.0/topics/vi.dist
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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