RNAMagnetBase: Low-level function to run core RNA magnet steps

In veltenlab/rnamagnet: Infers physical and signaling interactions from single-cell RNA-seq data

Description

Users are advised to use the top-level functions RNAMagnetAnchors and RNAMagnetSignaling which appropriately set default parameters and return user-friendly return values. This is a low level function for development purposes.

Usage

RNAMagnetBase(seurat, anchors = NULL, neighborhood.distance = NULL,
  neighborhood.gradient = NULL, .k = 10, .x0 = 0.5, .minExpression,
  .version = "latest", .cellularCompartment,
  .manualAnnotation = "Correct", .symmetric = F)

Arguments

seurat	An object of class seurat containing a valid clustering and t-SNE information. For information on how to create such an object, see https://satijalab.org/seurat/get_started.html
anchors	A character vector of anchor populations. Entries must be levels of seurat@ident. If NULL: All entries of seurat@ident are used as anchors.
neighborhood.distance	See RNAMagnetAnchors
neighborhood.gradient	See RNAMagnetAnchors
.k	Fuzzification parameter, see detail. Recommended to leave at the default value.
.x0	Fuzzification parameter, see detail. Recommended to leave at the default value.
.minExpression	Minimal expression level of genes to be included, specified as the number of cells in the dataset that express the gene.
.version	The version of the underlying ligand-receptor database. Recommended to leave at the default value. See getLigandsReceptors.
.cellularCompartment	Types of ligands to be included. For physical interactions, defaults to c("Membrane","ECM","Both"). See getLigandsReceptors.
.manualAnnotation	Annotation status of ligands to be included. Default to "Correct". See getLigandsReceptors.
.symmetric	Assume that if A is a receptor for B, B is also a receptor for A

Details

The algorithm takes the following steps:

1. Ligand-receptor pairs are selected based on the parameters .version, .cellularCompartment and .manualAnnotation. Choice of .cellularCompartment is crucial for determining the algorithm's behavior, e.g. if set to c("Secreted","Both"), paracrine signaling interactions involving soluble ligands are investigated.

2. Dropout values in the expression levels of ligands and receptors are imputed using magic

3. Mean expression level of ligands and receptors is computed for all anchor populations

4. For each cell or anchor population, the expression of each ligand and receptor is encoded as a fuzzy logic variable

5. Fuzzy logic AND is used to compute probabilities for a given interaction to be active between a single cell and an anchor population

6. An interaction score is computed as the sum of interaction probabilities across all possible ligand-receptor pairs

7. Specificty scores are computed by comparing interaction scores to average interaction scores in a local neighborhood.

Add the methods section of the paper here!

Value

Returns an object of class rnamagnet

veltenlab/rnamagnet documentation built on June 24, 2021, 6:19 p.m.