Get differentially expressed genes for Array B (one brain region)
Created: 2013-11-04 19:23:42
****IMPORTANT****:if libraries: library(ArrayExpress), library(hgu133b.db), library(limma) are not installed in the local R installation, then they need to be installed before running this workflow.
Original data come from Hodges et. al 2006 "Regional and cellular gene expression changes in human Huntington’s disease brain"
This workflow loads the two necessary files (gene expression data & phenotype data), and creates the expression set object to be used by the R package limma, to test for DE.
In this example we test for DE between HD and controls for each brain region. To test for DE between other variables, this information can be changed at the workflow "compute_DE_limma"
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Titles (1)
| Get differentially expressed genes for Array B (one brain region)
|
Descriptions (1)
| ****IMPORTANT****:if libraries: library(ArrayExpress), library(hgu133b.db), library(limma) are not installed in the local R installation, then they need to be installed before running this workflow.
Original data come from Hodges et. al 2006 "Regional and cellular gene expression changes in human Huntington’s disease brain"
This workflow loads the two necessary files (gene expression data & phenotype data), and creates the expression set object to be used by the R package limma, to test for DE.
In this example we test for DE between HD and controls for each brain region. To test for DE between other variables, this information can be changed at the workflow "compute_DE_limma"
|
Dependencies (0)
Inputs (4)
| Name |
Description |
| exprs_file |
Location of the gene expression data
|
| phenotypeData |
Location of the phenotype data
|
| cf |
This input port takes an integer 1 or 2 or 3, which represents the first, second or third coefficient that we want to export from top table (limma), when we test for differential expression.
We tested for DE between HD and normal tissue in each brain region. Therefore
cf = 1 -> caudate nucleus
cf = 2 -> frontal lobe
cf = 3 -> cerebellum
|
| working_dir |
the desired working directory. This workflow saves the results in .txt files and therefore
its useful for the user to provide a directory to save the results in.
|
Processors (7)
| Name |
Type |
Description |
| get_necessary_files |
rshell |
Loads the files we defined at the input ports. Gene expression and phenotypic data Script
#####################################################################################
###load the data to create the expression set object
#####################################################################################
setwd(datadirectory)
###read.tables
ex_file<-as.matrix(read.table(expression_file, header=TRUE, sep="\t", check.names=FALSE))
pheno_file<-read.table(phenotype_file, header=TRUE, sep="\t", check.names=FALSE) R Serverlocalhost:6311 |
| create_expression_set |
rshell |
create expression set object to be used by limma to test for DE Script##create expression set object
proceset<-new("ExpressionSet", exprs=ex_file)
rownames(pheno_file)<-pheno_file$Hybridization.Name
#all(rownames(pheno_a_test)==colnames(ex_a))
p_Data <- new("AnnotatedDataFrame", data = pheno_file)
proceset <- new("ExpressionSet", exprs = ex_file,phenoData = p_Data)
probe_ids<-rownames(exprs(proceset))
write.table(probe_ids, "probe_ids.txt", col.names=FALSE, row.names=FALSE)
print("expression set object done")
out1<-"blabla"R Serverlocalhost:6311 |
| libraries |
rshell |
Load necessary libraries.
If not existing libraries need to be installed beforehand.
these are :
library(ArrayExpress)
library(hgu133b.db)
library(limma) Scriptlibrary(ArrayExpress)
library(hgu133b.db)
#library("Biobase")
#library("limma")
R Serverlocalhost:6311 |
| compute_DE_limma |
workflow |
|
| probenames_to_entrez_genes_ids_Array_B |
rshell |
translates probe names to entrez gene ids. For array B. Script
##Get the matching gene ids for the probe ids
entrez_ids<-hgu133bENTREZID[probe_ids_new]
entrez_ids<-toTable(entrez_ids)
print("probe names to entrez_ids done")R Serverlocalhost:6311 |
| get_DE_genes |
workflow |
|
| cut_off |
stringconstant |
cut_off value for exporting DE genes.
Here it is defined as 0.05. for other p value cut offs this constant needs to be changed
Value0.05 |
Outputs (2)
| Name |
Description |
| filename_gene_ids |
|
| file_DE_genes |
|
Datalinks (8)
| Source |
Sink |
| phenotypeData |
get_necessary_files:phenotype_file |
| exprs_file |
get_necessary_files:expression_file |
| working_dir |
get_necessary_files:datadirectory |
| create_expression_set:probe_ids |
probenames_to_entrez_genes_ids_Array_B:probe_ids_new |
| cf |
get_DE_genes:cf |
| cut_off:value |
get_DE_genes:cut_off |
| get_DE_genes:filename |
filename_gene_ids |
| get_DE_genes:file_DE |
file_DE_genes |
Coordinations (7)
| Controller |
Target |
| compute_DE_limma |
get_DE_genes |
| libraries |
get_necessary_files |
| get_necessary_files |
create_expression_set |
| probenames_to_entrez_genes_ids_Array_B |
get_DE_genes |
| create_expression_set |
compute_DE_limma |
| create_expression_set |
probenames_to_entrez_genes_ids_Array_B |
| libraries |
create_expression_set |
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