ti_recat | R Documentation |
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"
)
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. |
A TI method wrapper to be used together with
infer_trajectory
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.
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