SlingshotDataSet
This was the original class for storing slingshot
results, but we now generally reommend using the
PseudotimeOrdering
class, instead. Most slingshot
functions will still work with SlingshotDataSet
objects, but will
return PseudotimeOrdering
objects, by default. To update old
SlingshotDataSet
objects, we have provided the
as.PseudotimeOrdering
conversion function. The only functions
that require SlingshotDataSet
objects are the plotting functions.
The SlingshotDataSet
class holds data relevant for
performing lineage inference with the slingshot
package, primarily a
reduced dimensional representation of the data and a set of cluster labels.
# S4 method for SlingshotDataSet
show(object)# S4 method for SlingshotDataSet,ANY
reducedDim(x)
# S4 method for SlingshotDataSet
reducedDims(x)
a SlingshotDataSet
object.
a SlingshotDataSet
object.
The accessor functions reducedDim
, clusterLabels
,
lineages
, adjacency
, curves
,
and slingParams
return the corresponding elements of a
SlingshotDataSet
. The functions slingPseudotime
and
slingCurveWeights
extract useful output elements of a
SlingshotDataSet
, provided that curves have already been fit with
either slingshot
or getCurves
.
show
: a short summary of a SlingshotDataSet
object.
reducedDim
: returns the matrix representing the reduced
dimensional dataset.
reducedDim
matrix. An n
by p
numeric matrix or data frame
giving the coordinates of the cells in a reduced dimensionality space.
clusterLabels
matrix or character. An n
by K
matrix of
weights indicating each cell's cluster assignment or a character vector of
cluster assignments, which will be converted into a binary matrix.
lineages
list. A list with each element a character vector of cluster names representing a lineage as an ordered set of clusters.
adjacency
matrix. A binary matrix describing the adjacency between clusters induced by the minimum spanning tree.
curves
list. A list of principal_curve
objects
produced by getCurves
.
slingParams
list. Additional parameters used by Slingshot. These may specify how the minimum spanning tree on clusters was constructed:
start.clus
character. The label of the root cluster, or a
vector of cluster labels giving the root clusters of each disjoint
component of the graph.
end.clus
character. Vector of cluster labels indicating
terminal clusters.
start.given
logical. A logical value
indicating whether the initial state was pre-specified.
end.given
logical. A vector of logical values indicating
whether each terminal state was pre-specified
omega
numeric or logical. Granularity parameter determining
the maximum edge length for building the MST. See
getLineages
.
omega_scale
numeric. Scaling factor used for setting maximum
edge length when omega = TRUE
. See getLineages
.
getCurves
:
shrink
logical or numeric between 0 and 1. Determines
whether and how much to shrink branching lineages toward their shared
average curve.
extend
character. Specifies the method for handling
root and leaf clusters of lineages when constructing the initial,
piece-wise linear curve. Accepted values are 'y' (default), 'n', and 'pc1'.
See getCurves
for details.
reweight
logical.
Indicates whether to allow cells shared
between lineages to be reweighted during curve-fitting. If TRUE
,
cells shared between lineages will be iteratively reweighted based on the
quantiles of their projection distances to each curve.
reassign
logical.
Indicates whether to reassign cells to lineages at each
iteration. If TRUE
, cells will be added to a lineage when their
projection distance to the curve is less than the median distance for all
cells currently assigned to the lineage. Additionally, shared cells will be
removed from a lineage if their projection distance to the curve is above
the 90th percentile and their weight along the curve is less than
0.1
.
shrink.method
character.
Denotes how to determine the amount of shrinkage for a branching lineage.
Accepted values are the same as for kernel
in the density
function (default is "cosine"
), as well as "tricube"
and
"density"
. See getCurves
for details.
approx_points numeric. Number of points to use in estimating
curves. See getCurves
for details.
allow.breaks logical. Whether to allow curves that diverge very early on in a trajectory to have different starting points.
Other parameters specified by
principal_curve
.