comparison normalize.r @ 2:f3fe0f64fe91 draft

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1:8389b0c211ae

#!/usr/bin/Rscript

#usage, options and doc goes here
argspec <- c("normalize.r - takes any flat file and normalizes the rows or the columns using various normalizations (median_shift, mean_shift, t_statistic (z-score), exp_fit, normal_fit, weibull_0.5_fit, weibull_1_fit, weibull_1.5_fit, weibull_5_fit). Requires a single header line and a single cloumn of annotation.
Usage:
    normalize.r input.tab norm_type norm_by > output.tab

			normals_numeric <- normals[2:length(normals[,1]),2:length(normals[1,])]
			normals_numeric <- apply(normals_numeric, 2, as.numeric)
			rownames(normals_numeric) <- normals[,1][2:length(normals[,1])]
			colnames(normals_numeric) <- normals[1,][2:length(normals[1,])]
			
			combined_matrix <- cbind(data_matrix, normals_numeric)
			tumor_indices <- c(1:length(data_matrix[1,]))
			normals_indices <- c(length(tumor_indices)+1:length(normals_numeric[1,]))
			data_matrix <- combined_matrix	
		}

2:f3fe0f64fe91

#!/usr/bin/Rscript

#Yulia Newton, last updated 20121217 v.3

#usage, options and doc goes here
argspec <- c("normalize.r - takes any flat file and normalizes the rows or the columns using various normalizations (median_shift, mean_shift, t_statistic (z-score), exp_fit, normal_fit, weibull_0.5_fit, weibull_1_fit, weibull_1.5_fit, weibull_5_fit). Requires a single header line and a single cloumn of annotation.
Usage:
    normalize.r input.tab norm_type norm_by > output.tab

			normals_numeric <- normals[2:length(normals[,1]),2:length(normals[1,])]
			normals_numeric <- apply(normals_numeric, 2, as.numeric)
			rownames(normals_numeric) <- normals[,1][2:length(normals[,1])]
			colnames(normals_numeric) <- normals[1,][2:length(normals[1,])]
			
			#select only the intersection of the rows between the two matrices:
			normals_numeric <- normals_numeric[rownames(normals_numeric) %in% rownames(data_matrix),]
			data_matrix <- data_matrix[rownames(data_matrix) %in% rownames(normals_numeric),]
			normals_numeric <- normals_numeric[order(rownames(normals_numeric)),]
			data_matrix <- data_matrix[order(rownames(data_matrix)),]
			
			combined_matrix <- cbind(data_matrix, normals_numeric)
			tumor_indices <- c(1:length(data_matrix[1,]))
			normals_indices <- c(length(tumor_indices)+1:length(normals_numeric[1,]))
			data_matrix <- combined_matrix	
		}