computePbnByCluster

computePbnBySingleCell

After running <code>performViper</code>, this can be run to produce a
PBN with the identity function probability for each node relative to the
VIPER normalised enrichment score (NES) for cell. For <code>computePbnByCluster</code>,
the median NES for all cells in that cluster will be used.

Given a gene regulatory boolean network and a RNA-seq dataset,
this package computes protein activity normalised enrichment scores
using 'VIPER', and then produces a probabilistic network using the scores
as probabilities for fixed node activation or deactivation,
in addition to the original Boolean functions.
For more information, refer to the preprint:
Victori and Buffa (2022) <doi:10.1101/2022.09.04.506528>.

Pedro Victori

ingres

Infer Gene Probabilistic Boolean Networks from Single-Cell Data

Francesca M. Buffa

computePbnByCluster function

<dl><dt>ingres.object</dt>
<dd>An <code>ingres</code> object with a
non-null VIPER slot.</dd>
<dt>range</dt>
<dd>A vector representing the range to which the NES are
to be re-scaled. <code>range[1]+range[2] == 0</code> should be TRUE.
Defaults to [-1, 1]</dd></dl>

Arguments

<ul>
<li><code>computePbnByCluster</code>: Compute a Probabilistic Boolean Network (PBN) for each cluster</li>
<li><code>computePbnBySingleCell</code>: Compute a Probabilistic Boolean Network (PBN) for each cell</li>
</ul>

Functions

Compute a Probabilistic Boolean Network (PBN) for each cluster or each cell — computePbnByCluster

<dl>

<dt>ingres.object</dt>
<dd>An <code>ingres</code> object with a
non-null VIPER slot.</dd>


<dt>range</dt>
<dd>A vector representing the range to which the NES are
to be re-scaled. <code>range[1]+range[2] == 0</code> should be TRUE.
Defaults to [-1, 1]</dd>

</dl>

computePbnByCluster: Compute a Probabilistic Boolean Network (PBN) for each cluster or each cell

Description

Usage

Value

Arguments

Functions

Examples