Description Usage Arguments Details Value

Learns a "trajectory" describing the biological process the cells are
going through, and calculates where each cell falls within that trajectory.
Monocle learns trajectories in two steps. The first step is reducing the dimensionality
of the data with `reduceDimension()`

. The second is this function.
function. This function takes as input a CellDataSet and returns it with
two new columns: `Pseudotime`

and `State`

, which together encode
where each cell maps to the trajectory. `orderCells()`

optionally takes
a "root" state, which you can use to specify the start of the trajectory. If
you don't provide a root state, one is selected arbitrarily.

1 | ```
orderCells(cds, root_state = NULL, num_paths = NULL, reverse = NULL)
``` |

`cds` |
the CellDataSet upon which to perform this operation |

`root_state` |
The state to use as the root of the trajectory. You must already have called orderCells() once to use this argument. |

`num_paths` |
the number of end-point cell states to allow in the biological process. |

`reverse` |
whether to reverse the beginning and end points of the learned biological process. |

The `reduction_method`

argument to `reduceDimension()`

determines which algorithm is used by `orderCells()`

to learn the trajectory.
If `reduction_method == "ICA"`

, this function uses *polygonal reconstruction*
to learn the underlying trajectory. If `reduction_method == "DDRTree"`

,
the trajectory is specified by the principal graph learned by the
`DDRTree()`

function.

Whichever algorithm you use, the trajectory will be composed of segments.
The cells from a segment will share the same value of `State`

. One of
these segments will be selected as the root of the trajectory arbitrarily.
The most distal cell on that segment will be chosen as the "first" cell in the
trajectory, and will have a Pseudotime value of zero. `orderCells()`

will
then "walk" along the trajectory, and as it encounters additional cells, it
will assign them increasingly large values of Pseudotime.

an updated CellDataSet object, in which phenoData contains values for State and Pseudotime for each cell

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