library.size.normalize

matrix (n_samples, n_dimensions)
2 dimensional input data array with n cells and p dimensions

data

boolean, default=FALSE. If true, print verbose output

verbose

Performs L1 normalization on input data such that the sum of expression
values for each cell sums to 1, then returns normalized matrix to the metric
space using median UMI count per cell effectively scaling all cells as if
they were sampled evenly.

PHATE is a tool for visualizing high dimensional single-cell data
with natural progressions or trajectories. PHATE uses a novel conceptual framework
for learning and visualizing the manifold inherent to biological systems in which
smooth transitions mark the progressions of cells from one state to another.
To see how PHATE can be applied to single-cell RNA-seq datasets from hematopoietic
stem cells, human embryonic stem cells, and bone marrow samples, check out our publication in Nature Biotechnology
at <doi:10.1038/s41587-019-0336-3>.

Scott Gigante

phateR

PHATE - Potential of Heat-Diffusion for Affinity-Based
Transition Embedding

Krishnan Srinivasan

library.size.normalize function

Performs L1 normalization on input data such that the sum of expression
values for each cell sums to 1, then returns normalized matrix to the metric
space using median UMI count per cell effectively scaling all cells as if
they were sampled evenly. — library.size.normalize

Performs L1 normalization on input data such that the sum of expression
values for each cell sums to 1, then returns normalized matrix to the metric
space using median UMI count per cell effectively scaling all cells as if
they were sampled evenly.

library.size.normalize: Performs L1 normalization on input data such that the sum of expression values for each cell sums to 1, then returns normalized matrix to the metric space using median UMI count per cell effectively scaling all cells as if they were sampled evenly.

Description

Usage

Arguments

Value