Mercurial > repos > ynewton > plot_distribution
diff plot_distribution.r @ 2:cf8d0d54bc78 draft
Uploaded
author | ynewton |
---|---|
date | Fri, 18 Jan 2013 12:18:04 -0500 |
parents | f91478b63ec6 |
children |
line wrap: on
line diff
--- a/plot_distribution.r Thu Dec 13 11:25:25 2012 -0500 +++ b/plot_distribution.r Fri Jan 18 12:18:04 2013 -0500 @@ -1,29 +1,14 @@ #!/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. +argspec <- c("plot_distribution.r - plots distribution of the value in the list or the matrix. Assumes the first line and the first column are annotations. Usage: - normalize.r input.tab norm_type norm_by > output.tab + plot_distribution.r input_matrix.tab output_file.pdf Example: - Rscript normalize.r test_matrix.tab median_shift column > output.tab - Rscript normalize.r test_matrix.tab mean_shift row normals.tab > output.tab + Rscript plot_distribution.r input_matrix.tab output_file.pdf Options: - input matrix (annotated by row and column names) - normalization type; available options: - median_shift - shifts all values by the median or the row/column if no normals are specified, otherwise shifts by the median of normals - mean_shift - shifts all values by the mean or the row/column if no normals are specified, otherwise shifts by the mean of normals - t_statistic - converts all values to z-scores; if normals are specified then converts to z-scores within normal and non-normal classes separately - exp_fit - (only by column) ranks data and transforms exponential CDF - normal_fit - (only by column) ranks data and transforms normal CDF - weibull_0.5_fit - (only by column) ranks data and transforms Weibull CDF with scale parameter = 1 and shape parameter = 0.5 - weibull_1_fit - (only by column) ranks data and transforms Weibull CDF with scale parameter = 1 and shape parameter = 1 - weibull_1.5_fit - (only by column) ranks data and transforms Weibull CDF with scale parameter = 1 and shape parameter = 1.5 - weibull_5_fit - (only by column) ranks data and transforms Weibull CDF with scale parameter = 1 and shape parameter = 5 - normalization by: - row - column - normals_file is an optional parameter which contains a list of column headers from the input matrix, which should be considered as normals - output file is specified through redirect character >") + input file name + output file name") read_matrix <- function(in_file){ header <- strsplit(readLines(con=in_file, n=1), "\t")[[1]] @@ -40,12 +25,15 @@ sink('/dev/null') input_data <- read_matrix(in_file) + input_data.df <- as.data.frame(input_data) + input_data.lst <- as.list(input_data.df) + input_data.unlst <- unlist(input_data.lst) + input_data.nona <- input_data.unlst[!is.na(input_data.unlst)] pdf(out_file, bg="white") par(mfrow=c(1,1)) - hist(input_data, col="lightblue", labels=TRUE, main="Histogram", xlab="") - plot(density(input_data), type="l", col="blue", main="Density") - dev.off() + hist(input_data.nona, col="lightblue", labels=TRUE, main="Histogram", xlab="") + plot(density(input_data.nona), type="l", col="blue", main="Density") + dev.off() } - main(commandArgs(TRUE)) \ No newline at end of file