diff --git a/python/recalAssociation.py b/python/recalAssociation.py
new file mode 100644
index 000000000..04d79d8a2
--- /dev/null
+++ b/python/recalAssociation.py
@@ -0,0 +1,90 @@
+from optparse import OptionParser
+from math import log10
+from math import floor
+
+def foreach( appl, col ):
+    for z in col:
+        appl(z)
+
+def parseWiggle(line):
+    return int(line.strip())
+
+def parseTDF(line):
+    return int(line.split("Q: ")[1].strip())
+
+def recalibrateJointly(files,JECDF):
+    print("Not implemented.")
+
+def recalibrate(fname,hist,out):
+    print(fname)
+    output = open(out + "." + fname.rsplit(".",1)[0].rsplit(".",1)[1], 'w')
+    denom = sum(hist)
+    cumQuals = dict()
+    for key1 in hist:
+        sumLess = 0
+        for key2 in hist:
+            if ( key2 <= key1 ):
+                sumLess += hist[key2]
+        cumQuals[key1] = int(-10*log10((0.0+sumLess)/denom))
+    use = parseTDF
+    if ( fname.endswith(".wig") ):
+        use = parseWiggle
+    inFile = open(fname)
+
+    if ( fname.endswith(".wig") ):
+        output.write(inFile.readline())
+
+    def rewrite(line,val):
+        if ( line.find("Q: ") == -1 ):
+            return str(val)+"\n"
+        else:
+            spline = line.split("Q: ")
+            bef = spline[0]
+            af = spline[1]
+            afSp = af.split("\t")
+            afSp[0] = str(val)
+            return bef + "\t".join(afSp)
+
+    foreach( lambda u: output.write(rewrite(u,cumQuals[use(u)])), inFile.readlines() )
+
+def run(opt,arg):
+    print(opt)
+    print(arg)
+    files = map(lambda u: open(u), opt.in_files)
+    fn = dict(zip(files,opt.in_files))
+    foreach( lambda u: u[1].readline(), filter( lambda u: u[0].endswith('.wig'), zip(opt.in_files,files)))
+    isWig = map(lambda u: u.endswith('.wig'), opt.in_files)
+    isWig = dict(zip(files,isWig))
+    marginalCumulativeDists = dict(map( lambda u: [u,dict()], opt.in_files))
+
+    def addVal(f,v):
+        d = marginalCumulativeDists[fn[f]]
+        if ( v not in d ):
+            d[v] = 0
+        d[v] += 1
+
+    def parseLine(fl,line):
+        if ( isWig[fl] ):
+            return parseWiggle(line)
+        else:
+            return parseTDF(line)
+
+    foreach( lambda f: foreach( lambda v: addVal(f,v), map(lambda u: parseLine(f,u), f.readlines() )), files )
+    foreach( lambda f: f.close(), files )
+    #print(marginalCumulativeDists)
+    if ( opt.joint ):
+        recalibrateJointly(opt.in_files,marginalCumulativeDists)
+    else:
+        foreach( lambda s: recalibrate(s,marginalCumulativeDists[s],opt.out), opt.in_files )
+
+def main():
+    usage = "usage: %prog [options] arg"
+    parser = OptionParser(usage)
+    parser.add_option("-I","--in",dest="in_files",help="file(s) to recalibrate",action="append")
+    parser.add_option("-J","--recalibrateJointly",dest="joint",action="store_true",help="Recalibrate quality scores jointly across files, rather than for each independently. Assumes lines match up exactly.")
+    parser.add_option("-O","--output",dest="out",action="store",help="The base name for the recalibrated output files")
+    (options,args) = parser.parse_args()
+    run(options,args)
+
+if __name__ == "__main__":
+    main()