Description Usage Arguments Value See Also Examples

View source: R/dimensionality_reduction.R

`reduce_dimensionality`

performs an eigenanalysis of the given dissimilarity matrix
and returns coordinates of the samples represented in an `ndim`

-dimensional space.

1 2 3 | ```
reduce_dimensionality(x, dist = c("pearson", "spearman", "cosine",
"euclidean", "manhattan"), ndim = 3, num_landmarks = 1000,
rescale = TRUE)
``` |

`x` |
a numeric matrix |

`dist` |
the distance metric to be used; can be any of the metrics listed in |

`ndim` |
the maximum dimension of the space which the data are to be represented in; must be in 1, 2, ..., n-1. |

`num_landmarks` |
the number of landmarks to be selected. |

`rescale` |
A logical indicating whether or not the returned space should be rescaled and centered. |

A matrix containing the coordinates of each sample, represented in an `ndim`

-dimensional space.

SCORPIUS

1 2 3 4 5 6 7 8 | ```
## Generate an example dataset
dataset <- generate_dataset(num_genes = 500, num_samples = 1000, num_groups = 4)
## Reduce the dimensionality of this dataset
space <- reduce_dimensionality(dataset$expression, ndim = 2)
## Visualise the dataset
draw_trajectory_plot(space, progression_group = dataset$sample_info$group_name)
``` |

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