reCAT

Will generate a trajectory using reCAT.

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

ti_recat(TSPFold = 2L, beginNum = 10L, endNum = 15L,
  step_size = 2L, base_cycle_range = c(6L, 9L), max_num = 300L,
  clustMethod = "GMM")

Arguments

TSPFold

No documentation provided by authors. Domain: U(2, 10). Default: 2. Format: integer.
beginNum

No documentation provided by authors. Domain: U(2, 20). Default: 10. Format: integer.
endNum

No documentation provided by authors. Domain: U(2, 20). Default: 15. Format: integer.
step_size

Determines the number of k to skip in your consensus path, ie ifstep_size = 2, then reCAT would only calculate and merge the paths fork = 12, 14, 16, 18, ..., n-2, n. We recommend step_size of up to a maximum of 5 while preserving the performance of reCAT. Usually a step_size of 2 (by default) would suffice and bigger steps are recommended for larger datasets (>1000 cells) in order to reduce computational time. Domain: U(2, 20). Default: 2. Format: integer.
base_cycle_range

. Domain: ( U(5, 10), U(5, 10) ). Default: (6, 9). Format: integer_range.
max_num

No documentation provided by authors. Domain: U(100, 500). Default: 300. Format: integer.
clustMethod

No documentation provided by authors. Domain: GMM, Pam, Kmeans. Default: GMM. Format: character.

Value

A TI method wrapper to be used together with infer_trajectory

References

Liu, Z., Lou, H., Xie, K., Wang, H., Chen, N., Aparicio, O.M., Zhang, M.Q., Jiang, R., Chen, T., 2017. Reconstructing cell cycle pseudo time-series via single-cell transcriptome data. Nature Communications 8.