BPstats.py

Copy and past the following into a text editor and save it as BPstats.py to use the script.
 * 1) !/usr/bin/env python


 * 1) BPstats.py [options]                                                                                    #
 * 2) Example: python BPstats.py -p -h myBasePile.txt                                                                           #
 * 3) Version: 1.2  Last Modified: 12/21/2009                                                                                   #
 * 4) >Ouptuts a txt file containing statistics in the following format:                                                        #
 * 5)   GSS basepile #\tGSS ref match length\ttarget match sum\tcoverage proportion\taverage density of target\tmedian densitiy #
 * 6) >Assumes each contig is 1000 bases long                                                                                   #
 * 7) Modifiers:                                                                                                                #
 * 8)   -d      : Save debug log                                                                                                #
 * 9)   -h      : Do not print header on first line                                                                             #
 * 10)   -p      : Print output to standard out (usually the shell being called from)                                            #
 * 11)   -r      : Make output more readable by adding extra tabs to the statistic columbs (aligns columbs to header)            #
 * 1)   -h      : Do not print header on first line                                                                             #
 * 2)   -p      : Print output to standard out (usually the shell being called from)                                            #
 * 3)   -r      : Make output more readable by adding extra tabs to the statistic columbs (aligns columbs to header)            #

import os, string, sys defArgList = ['BPstats.py','-H','C:/Python26/testData.txt'] #argument list used during script testing the with Python GUI IDLE argList    = sys.argv #argument list supplied by user argNum     = len(argList) #the number of arguments supplied minArgNum  = 1 #the smallest amount of arguments with which it is possible to run the script addHead    = True #is True if the headers are to be printed on the first line saveDubug  = False #is True if the debug is to be saved warning    = False #is set to 'True' if the program encounters any minor errors during the analysis; recorded in debug law readable   = False #is 'True' if the -r modifier is supplied; makes the output easier to read debugLog   = ['*********DEBUG LOG*********\n'] #where all errors/anamolies are recorded; saved if the -d modifier is supplied savePath   = './' #the directory in which the output will be saved defSavePath = 'C:/Python26/' #save path used during script testing with the python GUI IDLE header     = 'Contig #\tRef length\tMatch sum\tCoverage %\tAve density \tMed density\n' #the header which is printed on the first line of the output inData     = [] #a list of lists contiaing the data from the input file [[ref,density,actual],...] parsedData  = [] #a list containing data for each 1000 bp chunk [[GSS ref match length...see above]...] outData     = [] #a list of strings corresponding to each line in the output file modifiers   = [] #eventually contains a list of all modifiers and their arguments supplied by the user allMods     = 'hpr' #all the modifiers reconized by the script activeMods  = '' #a string contiaing all mods specified by the user modArgs     = [] #arguments supplied for the modifiers; assumed in the same order as the modifiers
 * 1) Imports / Variable Initilization##########################################################################################

def printHelp: print '/---\' print '| BPstats.py [options]                                               |' print '|---|' print '| Example: python BPstats.py -p -h myBasePile.txt                                      |' print '|---|' print '| Version: 1.2  Last Edited: 12/22/2009                                                |' print '|\t>Ouptuts a txt file containing statistics in the following format:                  |' print '|\t\tGSS basepile #, GSS ref match length, target match sum, coverage proportion,      |' print '|\t\taverage density of target, median densitiy                                        |' print '|\t>Assumes each contig is 1000 bases long                                             |' print '|---|' print '| Modifiers:                                                                           |' print '|\t-d\t: Save debug log                                                                |' print '|\t-h\t: Do not print header on first line                                             |' print '|\t-p\t: Print output to standard out (usually the shell being called from)            |' print '|\t-r\t: Make output more readable by adding extra tabs to the output columbs          |' print '\---/'

def errorExit: print 'The program was forced to exit prematurly, printing debug log...\n' for line in debugLog: print line sys.exit
 * 1) Error handling function#####################################################################################################
 * 2) >Is called when the script encounters a fatal error                                                                       #
 * 3) >Prints the debug log to standard out (usually the screen)                                                                #

if __name__ == '__main__': #If the program is being called independent of the Python GUI, IDLE...   if argNum > minArgNum: #If at least the minimum number of arguments necessary is supplied... if os.path.exists(argList[-1]) == 0: #if the path dose not exist debugLog.append('Error: Invalid file path to input data') errorExit #end the program elif argNum == 1: #If no arguments are supplied... helpOnly = True printHelp #prints help menu else: debugLog.append('Error: Too few arguments supplied\n') errorExit else: #If the script is being imported on to IDLE argList = defArgList #use default arguments argNum  = len(defArgList) if argNum == 1: #If no arguments are supplied... helpOnly = True printHelp #prints help menu savePath = defSavePath #sets the save path to the default, specified in the variable initialization section debugLog.append('Alert: defualt debugging input arguments are being used\n') if helpOnly == False: #if arguments were supplied... faPath = argList[-1] #the path to the fasta file containing the input data if argNum > minArgNum + 1: #if modifiers are present (i.e. more the minimum number of arguments) modifiers = argList[1:-minArgNum] #everything before the required arguments are modifiers and their arguments
 * 1) Argument Interprtation####################################################################################################
 * 2) >Parses the arguments supplied by the user, or the default values if the script is being run on IDLE                      #
 * 3) >If no arguments are given, the help menu is printed                                                                      #
 * 4) >Modifiers and their arguments are isolated from the raw input for later processing (in Modifier Interpretation)          #

if helpOnly == False: ###Modifier Interpretation############################################################################################### #>Parses any modifiers and modifier arguments determined by the previous section of code, "Argument Interpretation"    # #>Given arguments are compared against a list of known arguments                                                       # #>Matches found change the appropriate variable for the desired effect of the modifier the script                      # if len(modifiers) > 0: #if modifiers are supplied for mod in modifiers: #loops through the list of modifiers and modifier arguments if mod[0] == '-' and len(mod) == 2: #list entry considered modifier if it starts with - and is only two characters activeMods += mod[1:] #sorts the modifiers into activeMods... else: modArgs.append(mod) #assumes everything else to be a modifier argument for letter in activeMods: #loops through supplied modifiers if string.find(allMods,letter) == -1: #checks if the modifier is recognized by this script debugLog.append('Warning: Unexpected modifier: ' + letter + '\n') warning = True #if the input modifier is not found else: #if it is a recognized modifier...               if letter == 'd': #if -d is supplied... saveDebug = True #The debug log will be saved to the current working directory if letter == 'h': #if -h is supplied... printHead = False #header will not be included in the output if letter == 'p': #if -p is supplied... printOut = True #The results will be printed to the standard output (usually the screen) if letter == 'r': #if -r is supplied... readable = True #columbs are spaced in a more readable way #########################################################################################################################

###Input data parseing and file procedures############################################################################### inHandle = open(inPath, 'r') #creates a file object inHandle.readline #moves position past the header on the first line for line in inHandle: #loops through the lines of the input file lineParts = string.split(line) #produces a list of all the contents of each line (separated by spaces/abs) reference = lineParts[1] actual   = lineParts[6] density  = 0 for index in range(2,6): #adds the middle 4 values together to obtain density density += int(lineParts[index]) inData.append([reference,density,actual]) #adds parsed line to the list that will be analysed inHandle.close #closes the file object #outputs [[ref,density,actual],...]   #########################################################################################################################

###Statistical analysis################################################################################################## contigNum = len(inData)/1000 #The number of contigs the base pile output represents for count in range(0,contigNum): #do once for every contig contig = inData[count * 1000:(count + 1) * 1000] #isolates the parsed input data specific to that contig refMatchLen = 0 #records the index of the last known base on the reference tarMatchSum = 0 #counts how many known (not N) bases match the target medDensity = 0 #median density value for the contig index = 0 denList = [] #a list of all the densities for this contig; used to get median and average density for bp in contig: #for every base in the contig... denList.append(bp[1]) #record its density value if bp[0] != 'N': #if the actual value is known... refMatchLen = index #the length of the viable portion of the reference that is known if bp[2] != 'N' and bp[0] == bp[2]: #if the actual value is known and equals the reference...                    tarMatchSum += 1 #increment the amount of matching bases index += 1 #incremented to match the index of the current base pair denList.sort #allows for the median calculation coveragePro = float(tarMatchSum) / float(refMatchLen) #percentage of the actual that matchs to the reference aveDensity = float(sum(denList)) / float(refMatchLen) #average density values within the known portion of the reference medDensity = float(denList[499] + denList[500]) / 2 #median density of the entire range of density values contigStats = [] contigStats.append(count + 1)      #GSS basepile # contigStats.append(refMatchLen) contigStats.append(tarMatchSum) contigStats.append(coveragePro) contigStats.append(aveDensity) contigStats.append(medDensity) parsedData.append(contigStats) #outputs: [[GSS basepile #,GSS ref match length,target match sum,coverage proportion,average density of target,median densitiy]...]   #########################################################################################################################

def round(dec): #basic rounding function outDec = dec decPos = string.find(dec,'.') if decPos != -1 and len(dec) > (decPos + 3): outDec = outDec[:decPos + 3] return outDec

###Data-to-Text Formating################################################################################################ for contig in parsedData: #for every contig contigText = '' for stat in contig: #for every statistic in each contig statText = round(str(stat)) #round to three significant figures contigText += statText + '\t' #add the statistic to the output for this contig if readable: #if the -r modifier is supplied contigText += '\t' #add an extra tab to make the columbs align to the header contigText = contigText[:-1] #removes last \t if readable: #if the -r modifier is supplied contigText = contigText[:-1] #remove the extra tab contigText += '\n' #add an endline after the statistics of each contig outData.append(contigText) #add the contig to the output data #########################################################################################################################

###Out file writing and saveing procedures############################################################################### savePath += os.path.basename(inPath)[:-4] + '_stats.txt' #the path to where the output is saved outHandle = open(savePath, 'w') #opens the file object for saving the output for line in outData: #prints every line of outData to the output file... outHandle.write(line) outHandle.close if printOut: #if the -p modifier is supplied for line in outData: #prints every line to the standard output... print line[:-1] #########################################################################################################################