Merge pull request #91 from michaelmarty/v3

V3

GUniDec.spec

@@ -10,6 +10,7 @@ from multiprocessing import freeze_support
 from os import listdir
 from PyInstaller import compat
 import matplotlib
+import hashing
 
 freeze_support()
 
@@ -148,5 +149,7 @@ for root, dirs, files in os.walk(outputdir):
 zipf.close()
 print("Zipped to", zipdirectory, "from", outputdir)
 
+hashing.hashfile(zipdirectory)
+
 tend = time.perf_counter()
 print("Build Time: %.2gm" % ((tend - tstart) / 60.0))

PublicScripts/MutantCycleAnalysis/Step1_ListExtractor.py

@@ -0,0 +1,67 @@
+# Script to extract the peak areas from each deconvolved native mass spectrum
+# Note, you must first run UniDec on all the raw data to generate the deconvolved spectra
+# This can be done either individually or in batch
+
+import numpy as np
+import os
+import glob
+from unidec.modules.Extract2D import *
+
+R = 8.31446261815324 / 1000.
+units = "kJ/mol"
+
+#SpecifyingDirectory
+globaldir = "Z:\\Group Share\\Hiruni Jayasekera\\HSJ_MAE AqpZ CL\\Final2\\"
+
+os.chdir(globaldir)
+
+#ListExtractorProcessingParameters
+edges = [("WT", "W14A")]
+temps = [15, 20, 25, 30, 35, 40]
+width = 95
+method = 6
+params1 = [98590, 1400, 350, 0, 7, 0, 1, width, method]
+params2 = [98260, 1400, 680, 0, 7, 0, 1, width, method]
+params3 = [98260, 1400, 320, 0, 7, 0, 1, width, method]
+params4 = [98415, 1400, 500, 0, 7, 0, 1, width, method]
+params5 = [98706, 1400, 208, 0, 7, 0, 1, width, method]
+params = [params4]
+
+#SpecifyingPath
+app = wx.App(False)
+for ed in range(0, 1):
+    e1 = edges[ed][0]
+    e2 = edges[ed][1]
+    #if e2 is "DM":
+        #e2 = "R224-75A"
+    dirname = e1 + "_" + e2 + " Titrations All"
+    pathtop = os.path.join(globaldir, dirname)
+    print(os.path.isdir(pathtop), pathtop)
+    out = True
+
+    files = []
+    paths = []
+    datalist = []
+    # Loop through temperatures
+    for t in temps:
+        newpath = os.path.join(pathtop, e1 + "_" + e2 + "_" + str(t) + "C")
+        os.chdir(newpath)
+        temp = t
+        for path in glob.glob(f'{newpath}/*/**/', recursive=True):
+            mass_file = [f for f in os.listdir(path) if "_mass.txt" in f]
+            if len(mass_file) > 0:
+                mass_file = os.path.join(path, mass_file[0])
+                files.append(mass_file)
+                paths.append(path)
+                data = np.loadtxt(mass_file)
+                datalist.append(data)
+        print(files)
+        if len(files) < 0:
+            print("Failed at t=", t)
+            break
+    print(len(datalist))
+    # Load all data into the Extraction GUI, it will automatically export the required text files for Step 2 while
+    # Allowing users to check with the window that everything looks good. Just click next through all.
+    frame = Extract2DPlot(None, datalist, params=params[ed], directory=paths)
+    frame.on_all_next()
+    app.MainLoop()

PublicScripts/MutantCycleAnalysis/Step2_DeltaGToolWithErrorBars.py

@@ -0,0 +1,131 @@
+# Script to calculate DDG values from each quartet of extracted peak areas
+
+import matplotlib.pyplot as plt
+import numpy as np
+import os
+from matplotlib import rcParams
+import glob
+
+# rcParams['ps.useafm']=True
+rcParams['ps.fonttype'] = 42
+rcParams['pdf.fonttype'] = 42
+rcParams['lines.linewidth'] = 2
+rcParams['axes.linewidth'] = 1
+
+
+# rcParams['font.size']=8
+
+#Definition of Kd and delta(deltaG)
+def get_kd(mutant, wt, n=0, l=1, T=37):
+    a = wt[n]
+    al = wt[n + l]
+    b = mutant[n]
+    bl = mutant[n + l]
+    kd = a * bl / (al * b)
+    TK = T + 273.15
+    deltag = -R * TK * np.log(kd)
+    return kd, deltag, n
+
+
+R = 8.31446261815324 / 1000.
+units = "kJ/mol"
+# R = 1.98720425864083 / 1000.
+# units = "kcal/mol"
+
+# Data info
+temps = [15, 20, 25, 30, 35, 40]
+globaldir = "Z:\\Group Share\\Hiruni Jayasekera\\HSJ_MAE AqpZ CL\\Final2\\WT_R224A Titrations All\\WT_R224A_"
+fname = "Extract_grid_2D_Extract6.txt" # Sets the name of the file to be read in
+
+#Selecting txt files
+for t in temps:
+    temp = t
+    topdir = globaldir+str(t)+"C"
+    print(topdir)
+    files = []
+    for path in glob.glob(f'{topdir}/*/**/', recursive=True):
+        testpath = os.path.join(path,fname)
+        if os.path.isfile(testpath):
+            files.append(testpath)
+    print(files)
+    if len(files)<2:
+        print("Failed at t=", t)
+        break
+    kds = []
+    wts = []
+    mts = []
+    maxl = 7
+
+#Loading txt file data and normalization
+    fig, ax = plt.subplots()
+    for f in files:
+        data = np.loadtxt(f)
+
+        bm = data[:, 1] == 0
+        mutant = data[bm][:, 2]
+        wt = data[np.logical_not(bm)][:, 2]
+
+        wt = wt[:maxl]
+        mutant = mutant[:maxl]
+        wt = wt / np.sum(wt)
+        mutant = mutant / np.sum(mutant)
+        wts.append(wt)
+        mts.append(mutant)
+
+        ax.plot(np.arange(len(wt)) + 0.5, wt, color="g")
+        ax.plot(np.arange(len(mutant)), mutant, color="b")
+
+        # Calculate the DDG for each
+        kdlist = []
+        for n in range(0, maxl - 1):
+            for m in range(1, 2):# maxl - n):
+                value = get_kd(mutant, wt, n, m, T=temp)
+                kdlist.append(value)
+        kds.append(kdlist)
+
+    kds = np.array(kds)
+    wts = np.array(wts)
+    mts = np.array(mts)
+
+    # Get Mean and Std. Dev
+    wavg = np.mean(wts, axis=0)
+    mavg = np.mean(mts, axis=0)
+
+    wstd = np.std(wts, axis=0)
+    mstd = np.std(mts, axis=0)
+
+    #Printing Kd, ddG, ddG, n>n+1
+    print(kds)
+
+    # Make Plots
+    maxn = maxl
+    labels = ["0", "1", "2", "3", "4", "5", "6"]
+    ax.bar(np.arange(maxn), mavg[:maxn], 0.45, color="b", yerr=mstd[:maxn], capsize=3, label="Mutant")
+    ax.bar(np.arange(maxn) + 0.45, wavg[:maxn], 0.45, color="g", yerr=wstd[:maxn], capsize=3, label="WT")
+    ax.set_xticks(np.arange(maxn) + 0.225, labels=labels[:maxn])
+    ax.set_yticks([0, 0.5, 1.0], labels=["0", "%", "100"])
+    ax.spines['right'].set_visible(False)
+    ax.spines['top'].set_visible(False)
+    ax.set_ylim(0, 1.0)
+    ax.set_xlabel("Number of Bound Lipids")
+    ax.legend()
+    ax.set_title(str(t))
+
+    dgs = []
+
+    for n in range(0, maxn - 1):
+        avgdg = np.mean(kds[:, n, 1])
+        sddg = np.std(kds[:, n, 1])
+
+        dgvals = list(kds[:, n, 1])
+        dgvals.append(avgdg)
+        dgvals.append(sddg)
+
+        dgs.append(dgvals)
+        #ddG labels
+        text = "\u0394\u0394G = " + str(round(avgdg, 2)) + " \u00B1 " + str(round(sddg, 2)) + " " + units
+        ax.text(n, wavg[0] + 0.1 + 0.15 * n, text)
+    # Save results
+    np.savetxt(os.path.join(topdir, "DG_resultsN2_Fixed.txt"), dgs)
+    plt.savefig(os.path.join(topdir, "PlotN2_Fixed.pdf"))
+plt.show()