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Part 3: Exporting data
EwoudEwing edited this page May 10, 2019
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2 revisions
We can say we want just the clustered pathways, or we want to have a look at both the RR and the clustered pathways. It writes it in the folder assigned to file_location and it takes the name of Name and writes it into a CSV file with seperation of “;”, to make it readable by Excel.
IPA.files <- c(system.file("extdata",
"MM10.IPA.KO.uGvsMac.Canonical_pathways.xls",
package = "GeneSetCluster"),
system.file("extdata",
"MM10.IPA.WT.uGvsMac.Canonical_pathways.xls",
package = "GeneSetCluster"),
system.file("extdata",
"MM10.IPA.KO.uGvsMac.Functional_annotations.xls",
package = "GeneSetCluster"),
system.file("extdata",
"MM10.IPA.WT.uGvsMac.Functional_annotations.xls",
package = "GeneSetCluster"))
canonical.files <- IPA.files[grep("Canonical", IPA.files)]
IPA.object1 <- LoadGeneSets(file_location = canonical.files,
groupnames= c("KO", "WT"),
P.cutoff = 1.3,
Mol.cutoff = 5,
Source = "IPA",
type = "Canonical_Pathways",
structure = "SYMBOL",
seperator = ",")
IPA.object2 <- CombineGeneSets(Object = IPA.object1)
IPA.object3 <- ClusterGeneSets(Object = IPA.object2,
clusters = 12,
method = "kmeans")
WriteGeneSets(Object= IPA.object3,
file_location = getwd(),
name = "IPA_20181123", write = "Both")
Example Script: Example
Step 1A: Loading the data
Step 1B: Creating an Object
Step 2: Combine and Cluster
Step 2B: User supplied distance function
Step 2C: Highlighting-Genes
Step 3: Exporting Data
Step 4: Functional Investigation
Video: Step-by-step user guide