Created
October 16, 2015 08:55
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heatmap.r script with test data. Requires gplots. Run main() function after sourcing to make the heatmap.
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df <- data.frame(Row.Label= as.character(1:5) , Bio.marker=as.character(2:6), z=11:15, u=26:30) | |
df2 <- data.frame(Row.Label= as.character(1:5) , Bio.marker=as.character(2:6), z=11:15, u=26:30) | |
loaded_variables <- list("first one"=df, "second" = df2) | |
library(gplots) | |
dataset1color <- "coral3" | |
dataset2color <- "chartreuse3" | |
labelColumns <- c("Row.Label","Bio.marker") | |
#Input expected 1 or 2 dataframes ofwith columns: Row.Label, Bio.marker, ASSAY_0001 ASSAY_0002 ... | |
main <- function(){ | |
datasets <- parseInput(loaded_variables) #this will just make sure we have either 1 or 2 dataframes in a list | |
measurements <- extractMeasurements(datasets) #extract the numeric part - as a numeric matrix is needed for the heatmap.2 function | |
humanReadableNames <-extractNames(datasets) | |
measurements <- assignNames(measurements,humanReadableNames) #combine label with Biomarker(if present) and assign as a name to be displayed on the heatmap | |
measurements <- transform(measurements) #log2 transform the numerical matrix with measurements | |
grouping <- extractGrouping(datasets) #Grouping determines coloring of the samples - one color for dataset1 and a different one for dataset2 | |
makeHeatmap(measurements,grouping) # plot the heatmap and save it in the working directory as a .png file | |
} | |
parseInput <- function(variables){ | |
datasets <- list() | |
varLength <- length(variables) | |
if(varLength > 1){ | |
datasets <- list(dataset1 = variables[[1]], dataset2 = variables[[2]]) | |
} | |
else if(varLength == 1){ | |
datasets <- list(dataset1 = variables[[1]]) | |
} | |
return(datasets) | |
} | |
extractGrouping <- function(datasets){ | |
ds1Length <- ncol(datasets[[1]]) - length(labelColumns) | |
grouping <- rep(dataset1color,ds1Length) | |
if(length(datasets) > 1){ | |
ds2Length <- ncol(datasets[[2]]) - length(labelColumns) | |
secondSetGrouping <- rep(dataset2color,ds2Length) | |
grouping <- c(grouping,secondSetGrouping) | |
} | |
return(grouping) | |
} | |
extractMeasurements <- function(datasets){ | |
measurements <- extractMeasurement(datasets[[1]]) | |
if(length(datasets) > 1){ | |
secondDsMeasurements <-extractMeasurement(datasets[[2]]) | |
measurements <- cbind(measurements,secondDsMeasurements) | |
} | |
return(measurements) | |
} | |
extractMeasurement <- function(dataset){ | |
measurements <- subset(dataset,select=-c(Row.Label,Bio.marker)) # this will select all columns other than Row.Label,Bio.marker columns | |
measurements <- data.matrix(measurements) | |
} | |
assignNames <- function(measurements, humanReadableRowNames){ | |
rownames(measurements) <- humanReadableRowNames | |
return(measurements) | |
} | |
extractNames <- function(datasets){ | |
humanReadableNames <- datasets[[1]]$Row.Label | |
# if(length(datasets) > 1){ | |
# namesSecondDs <- datasets[[2]]$Row.Label | |
# humanReadableNames <- c(humanReadableNames, namesSecondDs) | |
# } | |
return(humanReadableNames) | |
} | |
transform <- function(measurements){ | |
measurements <- log(measurements,2) | |
} | |
makeHeatmap <- function(measurements,grouping){ | |
print(measurements) | |
png(filename="heatmap.png",width = 800,height=800) | |
heatmap.2(measurements, | |
scale = "none", | |
dendrogram = "none", | |
Rowv = NA, | |
Colv = NA, | |
density.info = "none", # histogram", # density.info=c("histogram","density","none") | |
trace = "none", | |
col=redgreen(75), | |
margins=c(12,12), | |
ColSideColors= as.character(grouping) | |
#adjCol=c("left","top") | |
) | |
dev.off() | |
} |
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