Tutorial:From Genefiltering to Results storgae in Microarray Analysis using in R (Part II) - FARMS
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4.9 years ago
majuang66 ▴ 120
# Start From Data import to Normalization in Microarray Analysis using in R (Part II) - FARMS
# biocLite ("farms")
# library (farms)
# mydata_GSE4536_farms <- qFarms(mydata_GSE4536)
# Genefiltering
INIs<-INIcalls(mydata_GSE4536_farms)

summary (INIs)
Informative probe sets:42.1%
non-informative probe sets:57.9%

# Get the results from INIs
I_data <- getI_Esets(INIs)

I_data
assyData:23,019 features, 101samples

#Save the above file
write.table(I_data,file="mydata_GSE4536_FARMS.txt",sep="\t",qoute=FALSE,row.names=TRUE,col.names=TRUE)

# Genefiltering using standard deviation
biocLite("genefilter")

library(genefilter)

# Genefilter use the format, matrix, not data.frame
# You can check your data format using class (I_data)
# I_data format is the ExpressionSet, so you convert the ExpressionSet to the matrix
I_data_1<-as.data.frame(I_data)
I_data_2<-as.matrix(I_data_1)
# transpose row to column
I_data_3<-t(I_data_3)
# Standard Deviation for row (features) more than 2
rsd <- rowSds(I_data_3)
i<-rsd>=2
summary(i)

mode - logical, FALSE-22979 genes, TRUE-41 genes, NA's - 0 genes
# Save the above file
GSE4536_qFarms_SD_filter <- I_data_3[i,]

write.table(GSE4536_qFarms_SD_filter, file="GSE4536_qFarms_SD_filter.txt",sep="\t",quote=FALSE,row.names=TRUE,col.names=TRUE)
# Standard Deviation for row (features) more than 1.5
rsd <- rowSds(I_data_3)
i_1<-rsd>=1.5

summary(i_1) 

mode - logical, FALSE-22808 genes, TRUE-212 genes, NA's - 0 genes
# Save the above file
GSE4536_qFarms_SD_filter_1 <- I_data_3[i_1,]

write.table(GSE4536_qFarms_SD_filter_1, file="GSE4536_qFarms_SD_filter_1.txt",sep="\t",quote=FALSE,row.names=TRUE,col.names=TRUE)
R gene Tutorial • 1.5k views
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Entering edit mode

FYI, there's a "tutorial" section. I've put your code in a code block and retagged this and your other recent post as tutorials. Thanks for contributing them!

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