Yeast stress response data

Description

This dataset was produced by Lucau-Danila et al. (2005). In this study the authors measured the changes in the mRNA concentrations for each gene at successive times after addition of an antimitotic drug (benomyl), in the growth media of Saccharomyces cerevisiae cells. Parallel experiments were conducted in different genetic contexts: the wild type strain and knock out (KO) strains in which the genes coding for different transcription factors connected to drug response (YAP1, PDR1, PDR3 and YRR1) were deleted. For 78 genes, the measured expression values for 5 different time points (at 30s, 2min, 4min, 10min and 20min) are available, in each yeast strains (WT, DeltaYAP1, DeltaPDR1, DeltaPDR3 and DeltaYRR1). These genes are divided into 18 clusters of genes with condordant transcription profiles. In this context, regulatory associations between parent and target genes are proposed if the deletion of a parent gene significantly alters the expression measurements of the target genes.

Usage

data(yeast)

Format

A list that comprises information for the 18 clusters of genes whose expression is identically modified in strains deleted for YAP1, PDR1, PDR3 and YRR1 transcription factors, compared to the wild type strain. Detailed description and more information concerning these clusters can be found in Lebre et al. (2010).

Cluster 1

Experimental data for genes that belong to the Cluster 1. yeast$Cluster1 is a list composed of the following elements: 1) yeast$Cluster1$InitialCluster: A matrix with in row the genes that belong to Cluster 1 and in column the different experimental measurements related to the wild type strain (WT), and strains deleted for the transcription factor YAP1 (DeltaYAP1), PDR1 (DeltaPDR1), PDR3 (DeltaPDR3) and YRR1 (DeltaYRR1). For each genetic context, 5 time points are available T1 = 30s, T2 = 2min, T3 = 4min, T4 = 10min and T5 = 20min. 2) yeast$Cluster1$targetData: A vector with all gene expression measurements correctly formatted to be analyzed with the ARTIVAsubnet function. 3) yeast$Cluster1$targetName: The name of the analyzed cluster. 4) yeast$Cluster1$GeneList: A vector with the names of the genes that belong to the analyzed cluster. 5) yeast$Cluster1$parentData: A matrix with in row the four transcription factors for which the corresponding genes were deleted (independantly) in knock out strains. 1 = the gene coding for the transcription factor is present and 0 = the gene coding for the transcription factor is deleted. This matrix is correctly formatted to be analyzed with the ARTIVAsubnet function, therefore searching for regulatory interactions between YAP1, PDR1, PDR3 and YRR1 transcription factors and the genes that belong to the analyzed cluster. 6) yeast$Cluster1$dataDescription : A vector indicating the ordering of the time measurements in the targetData and parentData variables.

Cluster2 to 18

Experimental data for genes that belong to the Cluster 2 to 18 (see the documentation for Cluster 1).

Source

Expression data were obtained from the website:

http://www.biologie.ens.fr/lgmgml/publication/benomyl/

References

The Early Expression of Yeast Genes Affected by Chemical Stress A. Lucau-Danila, G. Lelandais, Z. Kozovska, V. Tanty, T. Delaveau, F. Devaux and C. Jacq., Mol Cell Biol., 25(5):1860-8, 2005.

Statistical inference of the time-varying structure of gene regulation networks S. Lebre, J. Becq, F. Devaux, MP Stumpf, G. Lelandais., BMC Systems Biology 4:130, 2010.

Examples

####
# Datasets related to the analysis of the genomic response of the yeast 
# Saccharomyces cerevisiae to an environmental stress induced by 
# benomyl (a toxic compound).
# Analysis of the yeast data is presented in the original article of 
# ARTIVA (Lebre et al. BMC Syst. Biol, 2010)
####

# Load the yeast dataset
data(yeast)
# This is a a list that comprises information for the 18 clusters of genes
# whose expression is identically modified in strains deleted for
# YAP1, PDR1, PDR3 and YRR1 transcription factors,
# compared to the wild type strain.

# As an illustration : analysis of one cluster
cluster=4

# Different genes in a cluster is considered as repeated measurements.
# Organisation of the different time point measurements is described in
# variable : yeast[[cluster]]$dataDescription
# Beacause of repeated measurements, the minimum segment length is set to
# segMinLength = 1.
# The parentdata is the experiment design (YAP1, PDR1, PDR3 and YRR1
# deletion) described in variable: yeast[[cluster]]$parentData
# Time delay between parent and target genes is fixed to dyn=0.
## Not run: 
ARTIVAtest = ARTIVAsubnet(targetData = yeast[[cluster]]$targetData,
  targetName = yeast[[cluster]]$targetName,
  parentData = yeast[[cluster]]$parentData,
  parentNames = row.names(yeast[[cluster]]$parentData),
  dataDescription = yeast[[cluster]]$dataDescription,
  outputPath = paste("ARTIVA_Results_Cluster", cluster, sep = ""),
  dyn = 0,
  segMinLength = 1,
  edgesThreshold = 0.7,
  niter = 20000)

## End(Not run)
# Detailed results can be found in the folder named
# "ARTIVA_Results_Cluster4" (with the subfolders "Estimations" for
# detailled results of the estimated parameters and "Pictures" for
# graphical representations).

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(ARTIVA)
Loading required package: MASS
Loading required package: igraph

Attaching package: 'igraph'

The following objects are masked from 'package:stats':

    decompose, spectrum

The following object is masked from 'package:base':

    union

Loading required package: gplots

Attaching package: 'gplots'

The following object is masked from 'package:stats':

    lowess

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/ARTIVA/yeast.Rd_%03d_medium.png", width=480, height=480)
> ### Name: yeast
> ### Title: Yeast stress response data
> ### Aliases: yeast
> ### Keywords: datasets
> 
> ### ** Examples
> 
> ####
> # Datasets related to the analysis of the genomic response of the yeast 
> # Saccharomyces cerevisiae to an environmental stress induced by 
> # benomyl (a toxic compound).
> # Analysis of the yeast data is presented in the original article of 
> # ARTIVA (Lebre et al. BMC Syst. Biol, 2010)
> ####
> 
> # Load the yeast dataset
> data(yeast)
> # This is a a list that comprises information for the 18 clusters of genes
> # whose expression is identically modified in strains deleted for
> # YAP1, PDR1, PDR3 and YRR1 transcription factors,
> # compared to the wild type strain.
> 
> # As an illustration : analysis of one cluster
> cluster=4
> 
> # Different genes in a cluster is considered as repeated measurements.
> # Organisation of the different time point measurements is described in
> # variable : yeast[[cluster]]$dataDescription
> # Beacause of repeated measurements, the minimum segment length is set to
> # segMinLength = 1.
> # The parentdata is the experiment design (YAP1, PDR1, PDR3 and YRR1
> # deletion) described in variable: yeast[[cluster]]$parentData
> # Time delay between parent and target genes is fixed to dyn=0.
> ## Not run: 
> ##D ARTIVAtest = ARTIVAsubnet(targetData = yeast[[cluster]]$targetData,
> ##D   targetName = yeast[[cluster]]$targetName,
> ##D   parentData = yeast[[cluster]]$parentData,
> ##D   parentNames = row.names(yeast[[cluster]]$parentData),
> ##D   dataDescription = yeast[[cluster]]$dataDescription,
> ##D   outputPath = paste("ARTIVA_Results_Cluster", cluster, sep = ""),
> ##D   dyn = 0,
> ##D   segMinLength = 1,
> ##D   edgesThreshold = 0.7,
> ##D   niter = 20000)
> ## End(Not run)
> # Detailed results can be found in the folder named
> # "ARTIVA_Results_Cluster4" (with the subfolders "Estimations" for
> # detailled results of the estimated parameters and "Pictures" for
> # graphical representations).
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>