compute.spec.single

This is to calculate the similarity between:
1. the label propagation probability of cells for gene sets and
2. the identify of cells in a certain partition
This is called by 'compute.spec'; can also run by itself

Analysis frameworks for pathway heterogeneity and pathway activity evaluation in single-cell data, including scRNA-seq data and spatial genomics data.

Qingnan, Liang 

gsdensity

Density-Based Gene Set Specificity Evaluation

Ken Chen

compute.spec.single function

<dl><dt>vec</dt>
<dd>cell partition vector (usually a column name in object@meta.data)</dd>
<dt>positive</dt>
<dd>the positive label, e.g. "disease" or "cluster_1"</dd>
<dt>cell_df</dt>
<dd>the output of run.rwr.list</dd></dl>

Arguments

This is to calculate the similarity between:
1. the label propagation probability of cells for gene sets and
2. the identify of cells in a certain partition
This is called by 'compute.spec'; can also run by itself — compute.spec.single

<dl>

<dt>vec</dt>
<dd>cell partition vector (usually a column name in object@meta.data)</dd>


<dt>positive</dt>
<dd>the positive label, e.g. "disease" or "cluster_1"</dd>


<dt>cell_df</dt>
<dd>the output of run.rwr.list</dd>

</dl>

This is to calculate the similarity between:
1. the label propagation probability of cells for gene sets and
2. the identify of cells in a certain partition
This is called by 'compute.spec'; can also run by itself

compute.spec.single: This is to calculate the similarity between: 1. the label propagation probability of cells for gene sets and 2. the identify of cells in a certain partition This is called by 'compute.spec'; can also run by itself

Description

Usage

Value

Arguments