--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/src/MaaslinToGraphlanAnnotation.py	Tue May 13 22:00:40 2014 -0400
@@ -0,0 +1,213 @@
+#!/usr/bin/env python
+#####################################################################################
+#Copyright (C) <2012>
+#
+#Permission is hereby granted, free of charge, to any person obtaining a copy of
+#this software and associated documentation files (the "Software"), to deal in the
+#Software without restriction, including without limitation the rights to use, copy,
+#modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,
+#and to permit persons to whom the Software is furnished to do so, subject to
+#the following conditions:
+#
+#The above copyright notice and this permission notice shall be included in all copies
+#or substantial portions of the Software.
+#
+#THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
+#INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
+#PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+#HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
+#OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+#SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+#
+# This file is a component of the MaAsLin (Multivariate Associations Using Linear Models), 
+# authored by the Huttenhower lab at the Harvard School of Public Health
+# (contact Timothy Tickle, ttickle@hsph.harvard.edu).
+#####################################################################################
+
+__author__ = "Timothy Tickle"
+__copyright__ = "Copyright 2012"
+__credits__ = ["Timothy Tickle"]
+__license__ = ""
+__version__ = ""
+__maintainer__ = "Timothy Tickle"
+__email__ = "ttickle@sph.harvard.edu"
+__status__ = "Development"
+
+import argparse
+import csv
+import math
+from operator import itemgetter
+import re
+import string
+import sys
+
+#def funcGetColor(fNumeric,fMax):
+#  if fNumeric>0:
+#    return("#"+str(int(99*fNumeric/fMax)).zfill(2)+"0000")
+#  if fNumeric<0:
+#    return("#00"+str(int(99*abs(fNumeric/fMax))).zfill(2)+"00")
+#  return("#000000")
+
+def funcGetColor(fNumeric):
+  if fNumeric>0:
+    return sRingPositiveColor
+  else:
+    return sRingNegativeColor
+
+def funcGetAlpha(fNumeric,fMax):
+  return max(abs(fNumeric/fMax),dMinAlpha)
+
+#Constants
+sAnnotation = "annotation"
+sAnnotationColor = "annotation_background_color"
+sClass = "class"
+sRingAlpha = "ring_alpha"
+dMinAlpha = .075
+sRingColor = "ring_color"
+sRingHeight = "ring_height"
+#sRingHeightMin = 0.5
+sStandardizedRingHeight = "1.01"
+sRingLabel = "ring_label"
+sRingLabelSizeWord = "ring_label_font_size"
+sRingLabelSize = 10
+sRingLineColor = "#999999"
+sRingPositiveWord = "Positive"
+sRingPositiveColor = "#990000"
+sRingNegativeWord = "Negative"
+sRingNegativeColor = "#009900"
+sRingLineColorWord = "ring_separator_color"
+sRingLineThickness = "0.5"
+sRingLineThicknessWord = "ring_internal_separator_thickness"
+sCladeMarkerColor = "clade_marker_color"
+sCladeMarkerSize = "clade_marker_size"
+sHighlightedMarkerSize = "10"
+c_dMinDoubleValue = 0.00000000001
+
+#Set up arguments reader
+argp = argparse.ArgumentParser( prog = "MaaslinToGraphlanAnnotation.py",
+    description = """Converts summary files to graphlan annotation files.""" )
+
+#### Read in information
+#Arguments
+argp.add_argument("strInputSummary", metavar = "SummaryFile", type = argparse.FileType("r"), help ="Input summary file produced by maaslin")
+argp.add_argument("strInputCore", metavar = "CoreFile", type = argparse.FileType("r"), help ="Core file produced by Graphlan from the maaslin pcl")
+argp.add_argument("strInputHeader", metavar = "HeaderFile", type = argparse.FileType("r"), help ="Input header file to append to the generated annotation file.")
+argp.add_argument("strOutputAnnotation", metavar = "AnnotationFile", type = argparse.FileType("w"), help ="Output annotation file for graphlan")
+
+args = argp.parse_args( )
+
+#Read in the summary file and transform to class based descriptions
+csvSum = open(args.strInputSummary,'r') if isinstance(args.strInputSummary, str) else args.strInputSummary
+fSum = csv.reader(csvSum, delimiter="\t")
+#Skip header (until i do this a better way)
+fSum.next()
+
+#Extract associations (Metadata,taxon,coef,qvalue)
+lsAssociations = [[sLine[1],sLine[2],sLine[4],sLine[7]] for sLine in fSum]
+csvSum.close()
+
+#### Read in default graphlan settings provided by maaslin
+#Read in the annotation header file
+csvHdr = open(args.strInputHeader,'r') if isinstance(args.strInputHeader, str) else args.strInputHeader
+fHdr = csv.reader(csvHdr, delimiter="\t")
+
+#Begin writting the output
+#Output annotation file
+csvAnn = open(args.strOutputAnnotation,'w') if isinstance(args.strOutputAnnotation, str) else args.strOutputAnnotation
+fAnn = csv.writer(csvAnn, delimiter="\t")
+fAnn.writerows(fHdr)
+csvHdr.close()
+
+#If no associatiosn were found
+if(len(lsAssociations)==0):
+  csvAnn.close()
+
+else:
+  #### Fix name formats
+  #Manipulate names to graphlan complient names (clades seperated by .)
+  lsAssociations = sorted(lsAssociations, key=itemgetter(1))
+  lsAssociations = [[sBug[0]]+[re.sub("^[A-Za-z]__","",sBug[1])]+sBug[2:] for sBug in lsAssociations]
+  lsAssociations = [[sBug[0]]+[re.sub("\|*[A-Za-z]__|\|",".",sBug[1])]+sBug[2:] for sBug in lsAssociations]
+
+  #If this is an OTU, append the number and the genus level together for a more descriptive termal name
+  lsAssociationsModForOTU = []
+  for sBug in lsAssociations:
+    lsBug = sBug[1].split(".")
+    if(len(lsBug))> 1:
+      if(lsBug[-1].isdigit()):
+        lsBug[-2]=lsBug[-2]+"_"+lsBug[-1]
+        lsBug = lsBug[0:-1]
+      lsAssociationsModForOTU.append([sBug[0]]+[".".join(lsBug)]+sBug[2:])
+    else:
+      lsAssociationsModForOTU.append([sBug[0]]+[lsBug[0]]+sBug[2:])
+
+  #Extract just class info
+  #lsClassData = [[sLine[2],sClass,sLine[1]] for sLine in fSum]
+
+  ### Make rings
+  #Setup rings
+  dictRings = dict([[enumData[1],enumData[0]] for enumData in enumerate(set([lsData[0] for lsData in lsAssociationsModForOTU]))])
+
+  #Ring graphlan setting: rings represent a metadata that associates with a feature
+  #Rings have a line to help differetiate them
+  lsRingSettings = [[sRingLabel,lsPair[1],lsPair[0]] for lsPair in dictRings.items()]
+  lsRingLineColors = [[sRingLineColorWord,lsPair[1],sRingLineColor] for lsPair in dictRings.items()]
+  lsRingLineThick = [[sRingLineThicknessWord,lsPair[1],sRingLineThickness] for lsPair in dictRings.items()]
+  lsRingLineLabelSize = [[sRingLabelSizeWord,lsPair[1], sRingLabelSize] for lsPair in dictRings.items()]
+
+  #Create coloring for rings color represents the directionality of the relationship
+  dMaxCoef = max([abs(float(sAssociation[2])) for sAssociation in lsAssociationsModForOTU])
+  lsRingColors = [[lsAssociation[1], sRingColor, dictRings[lsAssociation[0]], funcGetColor(float(lsAssociation[2]))] for lsAssociation in lsAssociationsModForOTU]
+  lsRingAlpha = [[lsAssociation[1], sRingAlpha, dictRings[lsAssociation[0]], funcGetAlpha(float(lsAssociation[2]), dMaxCoef)] for lsAssociation in lsAssociationsModForOTU]
+
+  #Create height for rings representing the log tranformed q-value?
+  dMaxQValue = max([-1*math.log(max(float(sAssociation[3]), c_dMinDoubleValue)) for sAssociation in lsAssociationsModForOTU])
+  #lsRingHeights = [[lsAssociation[1], sRingHeight, dictRings[lsAssociation[0]], ((-1*math.log(max(float(lsAssociation[3]), c_dMinDoubleValue)))/dMaxQValue)+sRingHeightMin] for lsAssociation in lsAssociationsModForOTU]
+  lsRingHeights = [[lsAssociation[1], sRingHeight, dictRings[lsAssociation[0]], sStandardizedRingHeight] for lsAssociation in lsAssociationsModForOTU]
+
+  #### Marker
+  # Marker colors (mainly to make legend
+  lsMarkerColors = [[lsAssociation[1], sCladeMarkerColor, funcGetColor(float(lsAssociation[2]))] for lsAssociation in lsAssociationsModForOTU]
+  lsMarkerSizes = [[lsAssociation[1], sCladeMarkerSize, sHighlightedMarkerSize] for lsAssociation in lsAssociationsModForOTU]
+
+  #### Make internal highlights
+  #Highlight the associated clades
+  lsUniqueAssociatedTaxa = sorted(list(set([lsAssociation[1] for lsAssociation in lsAssociationsModForOTU])))
+
+  lsHighlights = []
+  sABCPrefix = ""
+  sListABC = string.ascii_lowercase
+  iListABCIndex = 0
+  for lsHighlight in lsUniqueAssociatedTaxa:
+    lsTaxa = lsHighlight.split(".")
+    sLabel = sABCPrefix+sListABC[iListABCIndex]+":"+lsTaxa[-1] if len(lsTaxa) > 2 else lsTaxa[-1]
+    lsHighlights.append([lsHighlight, sAnnotation, sLabel])
+    iListABCIndex = iListABCIndex + 1
+    if iListABCIndex > 25:
+      iListABCIndex = 0
+      sABCPrefix = sABCPrefix + sListABC[len(sABCPrefix)]
+
+  #Read in the core file
+  csvCore = open(args.strInputCore,'r') if isinstance(args.strInputCore, str) else args.strInputCore
+  fSum = csv.reader(csvCore, delimiter="\t")
+
+  #Add in all phylum just incase they were not already included here
+  lsAddSecondLevel = list(set([sUnique[0].split(".")[1] for sUnique in fSum if len(sUnique[0].split(".")) > 1]))
+  lsHighlights.extend([[sSecondLevel, sAnnotation, sSecondLevel] for sSecondLevel in lsAddSecondLevel])
+  lsHighlightColor = [[lsHighlight[0], sAnnotationColor,"b"] for lsHighlight in lsHighlights]
+
+  #### Write the remaining output annotation file
+  fAnn.writerows(lsRingSettings)
+  fAnn.writerows(lsRingLineColors)
+  fAnn.writerows(lsRingColors)
+  fAnn.writerows(lsRingAlpha)
+  fAnn.writerows(lsRingLineThick)
+  fAnn.writerows(lsRingLineLabelSize)
+  fAnn.writerows(lsRingHeights)
+  fAnn.writerows(lsMarkerColors)
+  fAnn.writerows(lsMarkerSizes)
+  fAnn.writerows([[sRingPositiveWord, sCladeMarkerColor, sRingPositiveColor]])
+  fAnn.writerows([[sRingNegativeWord, sCladeMarkerColor, sRingNegativeColor]])
+  fAnn.writerows(lsHighlights)
+  fAnn.writerows(lsHighlightColor)
+  csvAnn.close()