cellTree vem

Will generate a trajectory using cellTree vem.

This method was wrapped inside a container. The original code of this method is available here.

ti_celltree_vem(method = "VEM", sd_filter = 0.5,
  width_scale_factor = 1.5, outlier_tolerance_factor = 0.1,
  rooting_method = "null", num_topics = 4L, tot_iter = 1000000L,
  tolerance = 1e-05)

Arguments

method

LDA inference method to use. Domain: VEM. Default: VEM. Format: character.
sd_filter

Standard-deviation threshold below which genes should be removed from the data. Domain: e^U(-4.61, 1.61). Default: 0.5. Format: numeric.
width_scale_factor

A scaling factor for the dynamically-computed distance threshold (ignored if absolute_width is provided). Higher values will result in less branches in the backbone tree, while lower values might lead to a large number of backbone branches. Domain: e^U(-2.30, 4.61). Default: 1.5. Format: numeric.
outlier_tolerance_factor

Proportion of vertices, out of the total number of vertices divided by the total number of branches, that can be left at the end of the backbone tree-building algorithm. Domain: e^U(-9.21, 6.91). Default: 0.1. Format: numeric.
rooting_method

Method used to root the backbone tree. Must be either NULL or one of ‘longest.path’, ‘center.start.group’ or ‘average.start.group’. ‘longest.path’ picks one end of the longest shortest-path between two vertices. ’center.start.group’ picks the vertex in the starting group with lowest mean-square-distance to the others. ‘average.start.group’ creates a new artificial vertex, as the average of all cells in the starting group. If no value is provided, the best method is picked based on the type of grouping and start group information available. Domain: longest.path, center.start.group, average.start.group, null. Default: null. Format: character.
num_topics

Number of topics to fit in the model. Domain: U(2, 15). Default: 4. Format: integer.
tot_iter

Numeric parameters (optional) forwarded to the chosen LDA inference method's contol class. Domain: e^U(9.21, 16.12). Default: 1000000. Format: numeric.
tolerance

Numeric parameters (optional) forwarded to the chosen LDA inference method's contol class. Domain: e^U(-16.12, -6.91). Default: 1e-05. Format: numeric.

Value

A TI method wrapper to be used together with infer_trajectory

References

duVerle, D.A., Yotsukura, S., Nomura, S., Aburatani, H., Tsuda, K., 2016. CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data. BMC Bioinformatics 17.