GCAT5.0 released

2015-04-10 15:12:45 -05:00
commit 67544a10e6
257 changed files with 61661 additions and 0 deletions
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+    "contents" : "#Copyright 2012 The Board of Regents of the University of Wisconsin System.\n#Contributors: Jason Shao, James McCurdy, Enhai Xie, Adam G.W. Halstead, \n#Michael H. Whitney, Nathan DiPiazza, Trey K. Sato and Yury V. Bukhman\n#\n#This file is part of GCAT.\n#\n#GCAT is free software: you can redistribute it and/or modify\n#it under the terms of the GNU Lesser General Public License as published by\n#the Free Software Foundation, either version 3 of the License, or\n#(at your option) any later version.\n#\n#GCAT is distributed in the hope that it will be useful,\n#but WITHOUT ANY WARRANTY; without even the implied warranty of\n#MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n#GNU Lesser General Public License for more details.\n#\n#You should have received a copy of the GNU Lesser General Public License  \n#along with GCAT.  If not, see <http://www.gnu.org/licenses/>.\n\n# Wrapper for sapply to use lapply over an array, conserving the dimensions.\naapply = function(x, FUN,...){\n  dim.values = dim(x)\n\tdim.names = dimnames(x)\n\tx = lapply(x, function(x){FUN(x,...)})\n\tdim(x) = dim.values\n\tdimnames(x) = dim.names\n\treturn(x)\n\t}\n\n# A function to manually create an unchecked exception.\nexception = function(class, msg)\n{\n    cond <- simpleError(msg)\n    class(cond) <- c(class, \"MyException\", class(cond))\n    stop(cond)\n}\n",
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+    "contents" : "# Default NAMESPACE created by R\n# Remove the previous line if you edit this file\n\n# Export all names\nexportPattern(\".\")\n\n# Import all packages listed as Imports or Depends\nimport(\"pheatmap\", \"gplots\")\n",
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+    "contents" : "#Copyright 2012 The Board of Regents of the University of Wisconsin System.\n#Contributors: Jason Shao, James McCurdy, Enhai Xie, Adam G.W. Halstead,\n#Michael H. Whitney, Nathan DiPiazza, Trey K. Sato and Yury V. Bukhman\n#\n#This file is part of GCAT.\n#\n#GCAT is free software: you can redistribute it and/or modify\n#it under the terms of the GNU Lesser General Public License as published by\n#the Free Software Foundation, either version 3 of the License, or\n#(at your option) any later version.\n#\n#GCAT is distributed in the hope that it will be useful,\n#but WITHOUT ANY WARRANTY; without even the implied warranty of\n#MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n#GNU Lesser General Public License for more details.\n#\n#You should have received a copy of the GNU Lesser General Public License \n#along with GCAT.  If not, see <http://www.gnu.org/licenses/>.\n########################################################################\n#                                                                      #\n#  <model> class definition and functions. Objects contain equations   #\n#  and other information for parameterized growth curve models.        #\n#                                                                      #\n########################################################################\nsetClass(\"model\", representation(name = \"character\",\n                                 expression = \"expression\",\n                                 formula = \"formula\",\n                                 guess = \"function\"))\n# Slots:\n#   name - a simple description of the model.\n#   expression - an object of class \"expression\" that evaluates the response (transformed OD) with respect to the variable Time.\n#   formula - same as expression, but with y as the response.\n#   guess - a function that computes initial guesses for the parameters given a well object with a valid \"screen.data\" slot\n#           containing useable OD values and slope estimates\n# --------------------------------------------------------------------\n###################### BEGIN PROTOTYPING ACCESSOR METHODS##############\n\n# Minh: Let this code fragment be F1.\nif (!isGeneric(\"getName\")){\n  if (is.function(\"getName\"))\n    fun <- getName\n  else\n    fun <- function(object) standardGeneric(\"getName\")\n    setGeneric(\"getName\", fun)\n}\n# End of F1\nsetMethod(\"getName\", \"model\", function(object) object@name)\n\n# Minh: Let this line be F2.\nsetGeneric(\"getExpression\", function(object){standardGeneric(\"getExpression\")})\n# Question: How is F1 different from F2?\n\nsetMethod(\"getExpression\", \"model\",\n          function(object){\n            return(object@expression)\n          })\n\nsetGeneric(\"getFormula\", function(object){standeardGeneric(\"getFormula\")})\nsetMethod(\"getFormula\", \"model\", \n          function(object){\n            return(object@formula)\n          })\n\nsetGeneric(\"getGuess\", function(object){standeardGeneric(\"getGuess\")})\nsetMethod(\"getGuess\", \"model\", \n          function(object){\n            return(object@guess)\n          })\n######################## ENG PROTOTYPING ########################\n\n# Function to create a new model\n#' Model \n#' \n#' Function to create a new model \n#' @param name The name of the model \n#' @param expression Expression of the model \n#' @param formula The formula of this model \n#' @param guess The guess of this model \n#' @return The new model \nmodel = function(name, expression, formula, guess){\n  new(\"model\", name = name, expression = expression, formula = formula, guess = guess)\n}\n\nloess.g =  function(well,smooth.param=0.75){\n  #data = data.from(well)\n  #growth = data[,2]\n  #Time = data[,1]\n  Time = data.from(well)[,1]\n  \n  # predicted growth values to be used in estimating growth curve parameters\n  loess.fit = loess(data.from(well)[,2]~Time,span=smooth.param)\n  t = seq(from = min(Time), to = max(Time), by = (max(Time)-min(Time))/1000)\n  y = predict(loess.fit, data.frame(Time=t))\n  attr(y,\"names\") = NULL # need to remove the names to prevent them from showing up in the returned vector\n  \n  #  Remove any data points where y has not been estimated\n  filt = is.finite(y)\n  t = t[filt]\n  y = y[filt] # remove any NA etc\n  \n  # specific growth using loess to find max derivative\n  delta.t = diff(t)\n  dydt = diff(y)/delta.t\n  u = max(dydt)\n  \n  # lower and upper asymptotes\n  b = min(y)\n  A = max(y) - min(y)\n  \n  # inflection point\n  inflection.pt.index = which.max(dydt)\n  inflection.time = t[inflection.pt.index]\n  inflection.y = y[inflection.pt.index]\n  \n  # lag time\n  lam = inflection.time - (inflection.y-b)/u\n  \n  # Return named array of estimates\n  c(A = A, b = b, lam = lam, u = u)\n}\n\n\n",
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+    "contents" : "setwd(\"~/Downloads/\")\nfile.list = file.name = \"YPDAFEXglucoseTests_2-25-10.csv\"\nlayout.file = \"YPDAFEXglucoseTests_2-25-10_Layout.csv\"\nsingle.plate = T\nout.dir = getwd()\ngraphic.dir = paste(out.dir, \"/pics\", sep = \"\")\nadd.constant = 1\nblank.value = NULL\nstart.index = 2\ngrowth.cutoff = 0.05\nuse.linear.param = F\nuse.loess = F\nsmooth.param = 0.6\npoints.to.remove = 0\nremove.jumps = F\nsilent = F\nverbose = T\nreturn.fit = F\noverview.jpgs = T\nplate.nrow = 8\nplate.ncol = 12\ninput.skip.lines = 0\nmulti.column.headers = c(\"Plate ID\", \"Well\", \"OD\", \"Time\")\nsingle.column.headers = c(\"\",\"A1\")\nlayout.sheet.headers = c(\"Strain\", \"Media Definition\")\n\nt = gcat.analysis.main(file.list, single.plate, layout.file = NULL,   \n                   out.dir = getwd(), graphic.dir = paste(out.dir, \"/pics\", sep = \"\"), \n                   add.constant = 1, blank.value = NULL, start.index = 2, growth.cutoff = 0.05,\n                   use.linear.param=use.linear.param, use.loess=use.loess, smooth.param=0.1,\n                   points.to.remove = 0, remove.jumps = F, time.input = NA,\n                   plate.nrow = 8, plate.ncol = 12, input.skip.lines = 0,\n                   multi.column.headers = c(\"Plate.ID\", \"Well\", \"OD\", \"Time\"), single.column.headers = c(\"\",\"A1\"), \n                   layout.sheet.headers = c(\"Strain\", \"Media Definition\"),\n                   silent = F, verbose = F, return.fit = F, overview.jpgs = T)\n",
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