Added bfactor and max-bfactor-trace options to normweightmode

computePred.R

@@ -128,6 +128,15 @@ if((normWeightMode=="max-trace-pc") | (normWeightMode=="max-pc-trace")){
         trace<-append(trace, max(jet[row, "trace"], jet[row, "dfi"]))
     } 
   }
+} else if ((normWeightMode=="max-trace-bfactor") | (normWeightMode=="max-bfactor-trace")){
+  print(paste("Using ", normWeightMode))
+  for (row in 1:nrow(jet)) {
+    if(sum(colnames(jet)=="traceMax")==1){
+      trace<-append(trace, max(jet[row, "traceMax"], jet[row, "bfactor"]))
+    }else{
+        trace<-append(trace, max(jet[row, "trace"], jet[row, "bfactor"]))
+    } 
+  }
 }else if ((normWeightMode=="max-trace-pc-cv")|(normWeightMode=="max-trace-cv-pc")){
   print(paste("Using ", normWeightMode))
   for (row in 1:nrow(jet)) {
@@ -180,9 +189,14 @@ if((normWeightMode=="max-trace-pc") | (normWeightMode=="max-pc-trace")){
   for (row in 1:nrow(jet)) {
     trace<-append(trace, jet[row, "dfi"]) 
   }
+}else if (normWeightMode=="bfactor"){
+  print("Using only Bfactor values")
+  for (row in 1:nrow(jet)) {
+    trace<-append(trace, jet[row, "bfactor"]) 
+  }
 }else{
   print("ERROR: Unknown --normWeightMode selected!")
-  print("It can only be 'trace', 'pc', 'cv', 'dfi', 'max-trace-pc', 'max-trace-cv', 'max-trace-pc-cv' or 'half-cv+pc'!")
+  print("It can only be 'trace', 'pc', 'cv', 'dfi', 'bfactor', 'max-trace-pc', 'max-trace-cv', 'max-trace-pc-cv', 'half-cv+pc', 'max-trace-dfi' or 'max-trace-bfactor'!")
 }
 print(trace)
 
@@ -219,7 +233,7 @@ print(paste("Reading frequencies:"))
 for (row in 1:nrow(jet)) {
   frequencies<-append(frequencies, jet[row, "freq"] )
 }
-print(frequencies)
+#print(frequencies)
 freq_mean = mean(frequencies)
 
 #alpha = 0.6
@@ -238,7 +252,7 @@ for (row in 1:nrow(jet)) {
 #     alpha<-append(alpha, (1.0 - alpha_val))
 #   }  
 # }
-print(alpha)
+#print(alpha)
 
 
 

gemme.py

@@ -21,7 +21,7 @@ from gemmeAnal import *
 
 import pandas as pd
 
-def rankSortProteinData(dataArray):
+def rankSortProteinData(dataArray, inverted=True):
     """
         This function ranksorts protein data and converts it
         to values [0,1.0].
@@ -38,7 +38,10 @@ def rankSortProteinData(dataArray):
     normalizedRankedDataArray = rankdata(dataArray)/float(len(dataArray))
 
 #    np.savetxt(outfile, np.array([dataArray, normalizedRankedDataArray]).T)
-    return (1.0 - normalizedRankedDataArray)
+    if(inverted==True):
+        return (1.0 - normalizedRankedDataArray)
+    else:
+        return (normalizedRankedDataArray)
 
 def calcPercentDFI(pdbfile, outfile, nmodes=None, attenuate="true", ranksorted="true"):
     """
@@ -73,6 +76,68 @@ def calcPercentDFI(pdbfile, outfile, nmodes=None, attenuate="true", ranksorted="
     else:
         return dfi
 
+def calcBfactors(pdbfile, outfile, nmodes=None, attenuate="true", ranksorted="true"):
+    """
+        Calculate rank normalized dynamic flexibility index. 
+    """
+    
+    #confProDy(auto_show=False)
+
+    structure = parsePDB(pdbfile)
+    calphas = structure.select('name CA')
+
+    anm = ANM('ANM')
+    anm.buildHessian(calphas)
+    if(nmodes==None):
+        anm.calcModes(n_modes='all')
+    else:
+        anm.calcModes(n_modes=int(nmodes))
+
+    bfactors = calcSqFlucts(anm)
+
+    percentBfactors = rankSortProteinData(bfactors, inverted=False)
+
+    if(attenuate.lower()=='true'):
+        percentBfactors = attenuateEndPoints(percentBfactors)
+
+    # if(outfile != None):
+    #     np.savetxt(outfile, percentBfactors)
+    # else:
+    #     np.savetxt(outfile, dfi)
+
+    if(ranksorted.lower()=='true'):
+        return percentBfactors
+    else:
+        return bfactors
+
+def getBfactors(pdbfile, outfile, nmodes=None, attenuate="true", ranksorted="true"):
+    """
+        Calculate rank normalized dynamic flexibility index. 
+    """
+    
+    #confProDy(auto_show=False)
+
+    structure = parsePDB(pdbfile)
+    calphas = structure.select('name CA')
+
+    bfactors = calphas.getBetas()
+
+    percentBfactors = rankSortProteinData(bfactors, inverted=False)
+
+    if(attenuate.lower()=='true'):
+        percentBfactors = attenuateEndPoints(percentBfactors)
+
+    # if(outfile != None):
+    #     np.savetxt(outfile, percentBfactors)
+    # else:
+    #     np.savetxt(outfile, dfi)
+
+    if(ranksorted.lower()=='true'):
+        return percentBfactors
+    else:
+        return bfactors
+
+    
 def attenuateEndPoints(dfi):
     """
         Reduce DFI on N and C terminals with a sigmoid function.
@@ -414,6 +479,7 @@ def doit(inAli,mutFile,retMet,bFile,fFile,n,N, jetfile, pdbfile, normWeightMode,
         (normWeightMode != 'cv') and \
         (normWeightMode != 'pc') and \
         (normWeightMode != 'dfi') and \
+        (normWeightMode != 'bfactor') and \
         (normWeightMode != 'max-trace-pc') and \
         (normWeightMode != 'max-pc-trace') and \
         (normWeightMode != 'max-pc-cv') and \
@@ -421,15 +487,18 @@ def doit(inAli,mutFile,retMet,bFile,fFile,n,N, jetfile, pdbfile, normWeightMode,
         (normWeightMode != 'max-trace-cv') and \
         (normWeightMode != 'max-cv-trace') and \
         (normWeightMode != 'max-trace-dfi') and \
+        (normWeightMode != 'max-trace-bfactor') and \
         (normWeightMode != 'max-dfi-trace') and \
+        (normWeightMode != 'max-bfactor-trace') and \
         (normWeightMode != 'max-trace-pc-cv') and \
         (normWeightMode != 'max-trace-cv-pc') and \
         (normWeightMode != 'half-pc+cv') and \
         (normWeightMode != 'half-cv+pc') and \
         (normWeightMode != 'max-trace-half-cv+pc') and \
         (normWeightMode != 'max-trace-half-pc+cv')):
-        print("ERROR: normWeightMode can only be 'trace', 'cv', 'pc', 'dfi', \n"+\
+        print("ERROR: normWeightMode can only be 'trace', 'cv', 'pc', 'dfi', bfactor,\n"+\
               "       'max-trace-pc', 'max-trace-dfi', 'max-pc-cv', "+\
+              "       'max-trace-bfactor'"+\
               "       'max-trace-cv', 'max-trace-pc-cv'"+\
               "       'half-cv+pc' or max-trace-half-cv+pc!")
         sys.exit(-1)
@@ -460,18 +529,45 @@ def doit(inAli,mutFile,retMet,bFile,fFile,n,N, jetfile, pdbfile, normWeightMode,
         print("done")
 
     #If a real pdb file is given, calculate dfi for the residues. 
-    if((pdbfile != None) and ((normWeightMode=='dfi') or (normWeightMode=='max-trace-dfi') or (normWeightMode=='max-dfi-trace'))):
-        print("Calculating %DFI data per residue!")
-        dfi = calcPercentDFI(pdbfile, outfile=None, nmodes=None, attenuate="true", ranksorted="true")
-        dfi = dfi
-        df = pd.read_table(prot+"_jet.res")
-        print(df)
+    if(((normWeightMode=='dfi') or (normWeightMode=='max-trace-dfi') or (normWeightMode=='max-dfi-trace'))):
+        if (pdbfile != None):
+            print("ERROR: There is not any pdb file to calculate DFI.")
+            sys.exit(-1)
+        else:
+            print("Calculating %DFI data per residue!")
+            dfi = calcPercentDFI(pdbfile, outfile=None, nmodes=None, attenuate="true", ranksorted="true")
+            dfi = dfi
+            df = pd.read_table(prot+"_jet.res")
+            print(df)
 
-        df['dfi'] = dfi.round(4)
-        df.to_csv(prot+"_jet.res", header=True, index=None, sep='\t', mode='w')
+            df['dfi'] = dfi.round(4)
+            df.to_csv(prot+"_jet.res", header=True, index=None, sep='\t', mode='w')
 
-        print(df)
+            print(df)
 
+
+    #If a real pdb file is given, calculate or get Bfactors for the residues. 
+    if(((normWeightMode=='bfactor') or (normWeightMode=='max-trace-bfactor') or (normWeightMode=='max-bfactor-trace'))):
+        isCalc = False
+        if (pdbfile != None):
+            print("ERROR: There is not any pdb file to calculate or get Bfactors!")
+            sys.exit(-1)
+        else:
+            print("Calculating or getting Bfactor data per residue!")
+            if (isCalc):
+                bfactors = calcBfactors(pdbfile, outfile=None, nmodes=None, attenuate="true", ranksorted="true")
+            else:
+                bfactors = getBfactors(pdbfile, outfile=None, nmodes=None, attenuate="true", ranksorted="true")
+
+            bfactors = bfactors
+            df = pd.read_table(prot+"_jet.res")
+            print(df)
+
+            df['bfactor'] = bfactors.round(4)
+            df.to_csv(prot+"_jet.res", header=True, index=None, sep='\t', mode='w')
+
+            print(df)
+        
     launchPred(prot,inAli,mutFile, normWeightMode, alphabet)
 
     #Do Python plotting here
@@ -512,7 +608,7 @@ def doit(inAli,mutFile,retMet,bFile,fFile,n,N, jetfile, pdbfile, normWeightMode,
             print("       Can not generate "+prot+"_normPred_evolCombi.png file!")
         print("done")
 
-    #cleanTheMess(prot,bFile,fFile, chainID=chains[0])
+    cleanTheMess(prot,bFile,fFile, chainID=chains[0])
 
 
 def main():

pred.R

@@ -354,7 +354,6 @@ computePredSimple<-function(mat, distTrace, wt, thresh){
     for(a in aa){
       if(a!=wt[i]){
         sel = which(mat[,i]==a)
-<<<<<<< HEAD
         # print(sel)
         if(length(sel)>0){
           sortedDist=sort(distTrace[sel-1])
@@ -367,9 +366,7 @@ computePredSimple<-function(mat, distTrace, wt, thresh){
             }
           
           }
-=======
         if(length(sel)>0){sortedDist=sort(distTrace[sel-1])}
->>>>>>> parent of bd075e8... Added mt.20.txt, namely full alphabet!
         else{sortedDist = c()}
         res = c(res,findMinDist(sortedDist,thresh))
       }