overExprAnalysis: Perform in-silico over expression analysis

In TheJacksonLaboratory/sRACIPE_dev: Systems biology tool to simulate gene regulatory circuits

Description

Calculates the fraction of models in different clusters with full parameter range and on a subset of models with high production rate of a specific gene representing the over expression of the specific gene.

Usage

overExprAnalysis(topologyDf = topology, dataFile = output_file,
  paramFile = parameters_file, overProduction = 30, nClusters = 2,
  clusterOfInterest = 2, plotFilename = plot_filename,
  plotHeatmap = TRUE, plotBarPlot = TRUE, clusterCut = cluster_cut,
  plotToFile = TRUE)

Arguments

topologyDf	(optional) Deprecated. Topology (list) generated by sRACIPE_load_topology function
dataFile	(optional) Deprecated. Gene expression file (character).
paramFile	(optional) Deprecated. Parameter file (character).
overProduction	(optional) Percentage to which production rate decreases on knockdown. Uses a default value of 10 percent.
nClusters	(optional) Number of clusters in the data. Uses a default value of 2.
clusterOfInterest	(optional) cluster number (integer) to be used for arranging the transcription factors
plotFilename	(optional) Name of the output file. Uses the topology name as default.
rSet	(optional) List. A list returned by simulateGRC function.
cluster	assignments of the models

Value

List containing fraction of models in different clusters in the original simulations and after knowcking down different genes. Additionaly, it generates two pdf files in the results folder. First is barplot showing the percentage of different clusters in the original simulations and after knocking down each gene. The second pdf contains the heatmap of clusters after marking the models with cluster assignments.

Related Functions

simulateGRC, knockdownAnalysis, overExprAnalysis, plotData, calcHeatmapSimilarity

TheJacksonLaboratory/sRACIPE_dev documentation built on May 7, 2019, 8:16 a.m.