applySimplePPT: Applies the Simple PPT algorithm onto the expression data.

In YosefLab/VISION: Functional interpretation of single cell RNA-seq latent manifolds

Applies the Simple PPT algorithm onto the expression data.

Description

Applies the Simple PPT algorithm onto the expression data.

Usage

applySimplePPT(
  exprData,
  numCores,
  permExprData = NULL,
  nNodes_ = round(sqrt(nrow(exprData))),
  sigma = 0,
  gamma = 0
)

Arguments

exprData	Expression data – Num_Genes x Num_Samples
numCores	Number of cores to use during this analysis
permExprData	a list of permutated expression datasets, to use for significance estimation of the tree [default:NULL]
nNodes_	Number of nodes to find. Default is sqrt(N)
sigma	regularization parameter for soft-assignment of data points to nodes, used as the variance of a guassian kernel. If 0, this is estimated automatically
gamma	graph-level regularization parameter, controlling the tradeoff between the noise-levels in the data and the graph smoothness. If 0, this is estimated automatically.

Value

Information on the fitten tree

• C: spatial positions of the tree nodes in NUM_PROTEINS dimensional space

• W: Unweighted (binary) adjacency matrix of the fitten tree

• distMat: distance matrix between each tree node to each datapoint

• mse: the Mean-Squared-Error of the fitten tree

• zscore: a significance score for the fitted tree

YosefLab/VISION documentation built on June 14, 2024, 5:27 p.m.