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Got the lasso genes from Thams data. Also analyzed the distribution o…
…f those columns.
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library(ggplot2) | |||
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############################# | |||
# Load Data | |||
############################# | |||
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base_path <- '/home/reynaldo/Documents/School/Fall2017/DataMining/grp_proj/mkdataset/' | |||
file_name <- 'datasets/gan_datasets/tham_lasso_dataset.csv' | |||
all_data <- read.csv(paste(base_path, file_name, sep=''), header=TRUE) | |||
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gene_list_file_name <- 'human_mouse_gene_lists/lasso_gene_list.csv' | |||
gene_list <- read.csv(paste(base_path, gene_list_file_name, sep=''), header=TRUE) | |||
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################################ | |||
# Functions | |||
################################ | |||
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# Function from https://stackoverflow.com/questions/22742737/function-to-save-ggplot | |||
# Special Thanks to enricoferrero | |||
# https://stackoverflow.com/users/1540663/enricoferrero | |||
savePlot <- function(myPlot, file_name) { | |||
png(paste(file_name, '.png', sep=''), width=732, height=543) | |||
print(myPlot) | |||
dev.off() | |||
} | |||
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################################ | |||
# Variables | |||
################################ | |||
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# Vector of fields to examine | |||
# columns_to_exclude <- c('test', 'class') | |||
# fields <- colnames(all_data)[match(columns_to_exclude, colnames(all_data))] | |||
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for (field in gene_list$Symbol) { | |||
if (field %in% colnames(all_data)) { | |||
the_title <- paste('Expression Historgram of', field) | |||
x_lab <- paste(field, 'Expression Value') | |||
the_plot <- ggplot(all_data, aes(x=all_data[ , field])) + | |||
geom_histogram() + | |||
geom_vline(xintercept=mean(all_data[ , field]), color='red', size=2) + | |||
labs(title=the_title, x=x_lab) | |||
print(the_plot) | |||
savePlot(the_plot, field) | |||
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# Pause until ready for next | |||
readline("Press Enter for next") | |||
} | |||
} | |||
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