Will generate a trajectory using FateID.
This method was wrapped inside a container. The original code of this method is available here.
ti_fateid(reclassify = TRUE, clthr = 0.9, nbfactor = 5L, q = 0.75, k = 3L, m = "tsne", minnr = 5L, minnrh = 10L, trthr = 0.4, force = FALSE, run_environment = NULL)
| reclassify | logical; Whether to reclassify the cell grouping |
|---|---|
| clthr | numeric; Real number between zero and one. This is the threshold
for the fraction of random forest votes required to assign a cell not contained
within the target clusters to one of these clusters. The value of this
parameter should be sufficiently high to only reclassify cells with a
high-confidence assignment. Default value is 0.9. (default: |
| nbfactor | integer; Positive integer number. Determines the number of
trees grown for each random forest. The number of trees is given by the number
of columns of th training set multiplied by |
| q | numeric; Q real value between zero and one. This number specifies a
threshold used for feature selection based on importance sampling. A reduced
expression table is generated containing only features with an importance
larger than the q-quantile for at least one of the classes (i. e. target
clusters). Default value is 0.75. (default: |
| k | integer; Number of dimensions (default: |
| m | discrete; Dimensionality reduction method to use. Can be tsne, cmd, dm
or lle (default: |
| minnr | integer; Integer number of cells per target cluster to be selected
for classification (test set) in each round of training. For each target
cluster, the |
| minnrh | integer; Integer number of cells from the training set used for
classification. From each training set, the |
| trthr | numeric; Real value representing the threshold of the fraction of
random forest votes required for the inclusion of a given cell for the
computation of the principal curve. If |
| force | logical; Do not use! This is a parameter to force FateID to run on benchmark datasets where not enough end groups are present. |
| run_environment | In which environment to run the method, can be |
A TI method wrapper to be used together with
infer_trajectory
Herman, J.S., Sagar, Grün, D., 2018. FateID infers cell fate bias in multipotent progenitors from single-cell RNA-seq data. Nature Methods 15, 379–386.