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view src/breadcrumbs/scripts/scriptPcoa.py @ 0:0de566f21448 draft default tip
v2
author | sagun98 |
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date | Thu, 03 Jun 2021 18:13:32 +0000 |
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#!/usr/bin/env python """ Author: Timothy Tickle Description: Make PCoA of an abundance file """ __author__ = "Timothy Tickle" __copyright__ = "Copyright 2012" __credits__ = ["Timothy Tickle"] __license__ = "" __version__ = "" __maintainer__ = "Timothy Tickle" __email__ = "ttickle@sph.harvard.edu" __status__ = "Development" import sys import argparse from src.AbundanceTable import AbundanceTable from src.Metric import Metric import csv import os from src.PCoA import PCoA #Set up arguments reader argp = argparse.ArgumentParser( prog = "scriptPcoa.py", description = """PCoAs an abundance file given a metadata.\nExample:python scriptPcoa.py -i TID -l STSite""" ) #Arguments #For table argp.add_argument("-i","--id", dest="sIDName", default="ID", help="Abundance Table ID") argp.add_argument("-l","--meta", dest="sLastMetadataName", help="Last metadata name") argp.add_argument("-d","--fDelim", dest= "cFileDelimiter", action= "store", default="\t", help="File delimiter, default tab") argp.add_argument("-f","--featureDelim", dest="cFeatureNameDelimiter", action= "store", metavar="Feature Name Delimiter", default="|", help="Feature delimiter") argp.add_argument("-n","--doNorm", dest="fDoNormData", action="store_true", default=False, help="Flag to turn on normalization") argp.add_argument("-s","--doSum", dest="fDoSumData", action="store_true", default=False, help="Flag to turn on summation") argp.add_argument("-p","--paint", dest="sLabel", metavar= "Label", default=None, help="Label to paint in the PCoA") argp.add_argument("-m","--metric", dest="strMetric", metavar = "distance", default = PCoA.c_BRAY_CURTIS, help ="Distance metric to use. Pick from braycurtis, canberra, chebyshev, cityblock, correlation, cosine, euclidean, hamming, spearman, sqeuclidean, unifrac_unweighted, unifrac_weighted") argp.add_argument("-o","--outputFile", dest="strOutFile", metavar= "outputFile", default=None, help="Specify the path for the output figure.") argp.add_argument("-D","--DistanceMatrix", dest="strFileDistanceMatrix", metavar= "strFileDistanceMatrix", default=None, help="Specify the path for outputing the distance matrix (if interested). Default this will not output.") argp.add_argument("-C","--CoordinatesMatrix", dest="strFileCoordinatesMatrix", metavar= "strFileCoordinatesMatrix", default=None, help="Specify the path for outputing the x,y coordinates matrix (Dim 1 and 2). Default this will not output.") # Unifrac arguments argp.add_argument("-t","--unifracTree", dest="istrmTree", metavar="UnifracTreeFile", default=None, help="Optional file only needed for UniFrac calculations.") argp.add_argument("-e","--unifracEnv", dest="istrmEnvr", metavar="UnifracEnvFile", default=None, help="Optional file only needed for UniFrac calculations.") argp.add_argument("-c","--unifracColor", dest="fileUnifracColor", metavar="UnifracColorFile", default = None, help="A text file indicating the groupings of metadata to color. Each line in the file is a group to color. An example file line would be 'GroupName:ID,ID,ID,ID'") argp.add_argument("strFileAbund", metavar = "Abundance file", nargs="?", help ="Input data file") args = argp.parse_args( ) #Read in abundance table abndTable = None if args.strFileAbund: abndTable = AbundanceTable.funcMakeFromFile(args.strFileAbund, cDelimiter = args.cFileDelimiter, sMetadataID = args.sIDName, sLastMetadata = args.sLastMetadataName, cFeatureNameDelimiter= args.cFeatureNameDelimiter) #Normalize if need if args.fDoSumData: abndTable.funcSumClades() #Sum if needed if args.fDoNormData: abndTable.funcNormalize() #Get the metadata to paint lsKeys = None if abndTable: lsKeys = abndTable.funcGetMetadataCopy().keys() if not args.sLabel else [args.sLabel] #Get pieces of output file if not args.strOutFile: if not args.strFileAbund: args.strOutFile = os.path.splitext(os.path.basename(args.istrmEnvr))[0]+"-pcoa.pdf" else: args.strOutFile = os.path.splitext(os.path.basename(args.strFileAbund))[0]+"-pcoa.pdf" lsFilePieces = os.path.splitext(args.strOutFile) # Make PCoA object # Get PCoA object and plot pcoa = PCoA() if(not args.strMetric in [Metric.c_strUnifracUnweighted,Metric.c_strUnifracWeighted]) and abndTable: pcoa.loadData(abndTable,True) # Optional args.strFileDistanceMatrix if not none will force a printing of the distance measures to the path in args.strFileDistanceMatrix pcoa.run(tempDistanceMetric=args.strMetric, iDims=2, strDistanceMatrixFile=args.strFileDistanceMatrix, istrmTree=args.istrmTree, istrmEnvr=args.istrmEnvr) # Write dim 1 and 2 coordinates to file if args.strFileCoordinatesMatrix: lsIds = pcoa.funcGetIDs() mtrxCoordinates = pcoa.funcGetCoordinates() csvrCoordinates = csv.writer(open(args.strFileCoordinatesMatrix, 'w')) csvrCoordinates.writerow(["ID","Dimension_1","Dimension_2"]) for x in xrange(mtrxCoordinates.shape[0]): strId = lsIds[x] if lsIds else "" csvrCoordinates.writerow([strId]+mtrxCoordinates[x].tolist()) # Paint metadata if lsKeys: for iIndex in xrange(len(lsKeys)): lsMetadata = abndTable.funcGetMetadata(lsKeys[iIndex]) pcoa.plotList(lsLabelList = lsMetadata, strOutputFileName = lsFilePieces[0]+"-"+lsKeys[iIndex]+lsFilePieces[1], iSize=20, dAlpha=1.0, charForceColor=None, charForceShape=None, fInvert=False, iDim1=1, iDim2=2) if args.strMetric in [Metric.c_strUnifracUnweighted,Metric.c_strUnifracWeighted]: c_sNotGiven = "Not_specified" lsIds = pcoa.funcGetIDs() lsGroupLabels = [c_sNotGiven for s in lsIds] if args.fileUnifracColor: # Read color file and make a dictionary to convert ids lsColorLines = csv.reader(open(args.fileUnifracColor)) dictConvertIDToGroup = {} for lsLine in lsColorLines: if lsLine: sGroupID, sFirstID = lsLine[0].split(":") dictConvertIDToGroup.update(dict([(sID,sGroupID) for sID in [sFirstID]+lsLine[1:]])) lsGroupLabels = [dictConvertIDToGroup.get(sID,c_sNotGiven) for sID in lsIds] pcoa.plotList(lsLabelList = lsGroupLabels, strOutputFileName = lsFilePieces[0]+"-"+args.strMetric+lsFilePieces[1], iSize=20, dAlpha=1.0, charForceColor=None, charForceShape=None, fInvert=False, iDim1=1, iDim2=2)