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pre_Joinmap.py

+"""
+Scripted by Beiyu
+For joinmap pre-work
+To handle the grid with only nnxnp markers
+"""
+
+def parse(filename):
+    """
+    parse the txt tab file saved from excel
+    input:
+    filename: txt tab file, the head line should be the marker names in order, the first column should be individuals
+    genotype    marker1 marker2 ...
+    individual1 allele1 allele2 ...
+    individual2 allele3 allele4 ...
+    ... ... ... ...
+    output:
+    allele_dict: {individual: [alleles in order]}
+    markers: [markers]
+    """
+    f = open(filename,"r")
+    allele_dict = {}
+    for line in f:
+        if line.startswith("genotype"):
+            markers = line.split()[1:]
+        else:
+            individual = line.split()[0]
+            alleles = line.split()[1:]
+            allele_dict[individual] = alleles
+    return allele_dict, markers
+
+
+
+def nnxnp_table(allele_dict, markers):
+    """
+    convert the grid table to nnxnp table that can be used in Joinmap for CP population type
+    """
+    nnxnp_dict = {}
+    for individual in allele_dict:
+        nnxnp_dict[individual] = []
+        for i in range(len(markers)):
+            if allele_dict[individual][i] == "?":
+                nnxnp_dict[individual] += [""]
+            else:
+                a,b = allele_dict[individual][i].split(":")
+                if a == b:
+                    nnxnp_dict[individual] += ["nn"]
+                else:
+                    nnxnp_dict[individual] += ["np"]
+    return nnxnp_dict
+
+
+def axb_table(nnxnp_dict, markers):
+    """
+    convert the grid table to axb table that can be used in Joinmap for DH population type
+    """
+    axb_dict = {}
+    for individual in nnxnp_dict:
+        axb_dict[individual] = []
+        for i in range(len(markers)):
+            if nnxnp_dict[individual][i] == "nn":
+                axb_dict[individual] += ["a"]
+            elif nnxnp_dict[individual][i] == "np":
+                axb_dict[individual] += ["b"]
+            elif nnxnp_dict[individual][i] == "":
+                axb_dict[individual] += [""]
+    for i in range(1,len(markers)):
+        count_equal = 0
+        count_unequal = 0
+        for individual in axb_dict:
+            if axb_dict[individual][i] == axb_dict[individual][i-1] and axb_dict[individual][i] != "" and \
+                axb_dict[individual][i-1] != "":
+                count_equal += 1
+            elif axb_dict[individual][i] != axb_dict[individual][i-1] and axb_dict[individual][i] != "" and \
+                axb_dict[individual][i-1] != "":
+                count_unequal += 1
+        if count_equal < count_unequal:
+            for individual in axb_dict:
+                if axb_dict[individual][i] == "a":
+                    axb_dict[individual][i] = "b"
+                elif axb_dict[individual][i] == "b":
+                    axb_dict[individual][i] = "a"
+    return axb_dict
+
+def correct_markers(allele_dict, markers):
+    """
+    Remove the markers that do not show segregation or show 3 different alleles in the grid.
+    """
+    corrected_allele_dict = {}
+    corrected_markers = []
+    for individual in allele_dict:
+        corrected_allele_dict[individual] = []
+    for i in range(len(markers)):
+        alleles = []
+        for individual in allele_dict:
+            if allele_dict[individual][i] != "?" and allele_dict[individual][i] not in alleles:
+                alleles += [allele_dict[individual][i]]
+        if len(alleles) == 2:
+            corrected_markers += [markers[i]]
+            for individual in allele_dict:
+                corrected_allele_dict[individual] += [allele_dict[individual][i]]
+
+    return corrected_allele_dict, corrected_markers
+
+def correct_isolated_cells(allele_dict, axb_dict, markers):
+    """
+    Replace the isolated coloured cells with missing value
+    """
+    for individual in axb_dict:
+        for i in range(1, len(markers) - 1):
+            if axb_dict[individual][i] != "" and axb_dict[individual][i-1] != "" and axb_dict[individual][i+1] != "":
+                if axb_dict[individual][i] != axb_dict[individual][i-1] and \
+                    axb_dict[individual][i] != axb_dict[individual][i+1]:
+                    axb_dict[individual][i] = ""
+                    allele_dict[individual][i] = "?"
+    return allele_dict, axb_dict
+
+
+
+def output(filename):
+    f = filename.split(".")[0]
+    f1 = open(f + "_nnxnp.txt", "w")
+    f2 = open(f + "_axb.txt", "w")
+    f1.write("\t")
+    f2.write("\t")
+    allele_dict, markers = parse(filename)
+    allele_dict, markers = correct_markers(allele_dict, markers)
+    for marker in markers:
+        f1.write(marker + "\t")
+        f2.write(marker + "\t")
+    f1.write("\n\t" + "<nnxnp>\t" * len(markers) + "\n\n")
+    f2.write("\n")
+    nnxnp_dict = nnxnp_table(allele_dict, markers)
+    axb_dict = axb_table(nnxnp_dict, markers)
+    allele_dict, axb_dict = correct_isolated_cells(allele_dict, axb_dict, markers)
+    nnxnp_dict = nnxnp_table(allele_dict, markers)
+    for individual in nnxnp_dict:
+        f1.write("\n" + individual + "\t")
+        for value in nnxnp_dict[individual]:
+            f1.write(value + "\t")
+    for individual in axb_dict:
+        f2.write("\n" + individual + "\t")
+        for value in axb_dict[individual]:
+            f2.write(value + "\t")
+
+def reorder(filename):
+    """
+    reorder the grid by the positions of recombination breakpoints
+    """
+    allele_dict, markers = parse(filename)
+    allele_dict, markers = correct_markers(allele_dict, markers)
+    nnxnp_dict = nnxnp_table(allele_dict, markers)
+    axb_dict = axb_table(nnxnp_dict, markers)
+    allele_dict, axb_dict = correct_isolated_cells(allele_dict, axb_dict, markers)
+    index = {}
+    for individual in axb_dict:
+        count = 0
+        recombinant = False
+        i = 0
+        while recombinant == False and i < len(markers):
+            if count >= 0 and axb_dict[individual][i] == "a":
+                count += 1
+                i += 1
+            elif count <= 0 and axb_dict[individual][i] == "b":
+                count -= 1
+                i += 1
+            elif axb_dict[individual][i] == "":
+                if count == 0:
+                    i += 1
+                elif count > 0:
+                    count += 1
+                    i +=1
+                elif count < 0:
+                    count -= 1
+                    i +=1
+            else:
+                recombinant = True
+                index[individual] = count
+            if recombinant == False and i == len(markers) - 1:
+                if count > 0:
+                    index[individual] = len(markers)
+                else:
+                    index[individual] = -len(markers)
+    i = 0
+    order = []
+    while -len(markers) <= i:
+        for individual in index:
+            if index[individual] == i:
+                order += [individual]
+        i -= 1
+    i = 1
+    while len(markers) >= i:
+        for individual in index:
+            if index[individual] == i:
+                order += [individual]
+        i += 1
+    f = open(filename.split(".")[0] + "_reordered.txt", "w")
+    f.write("genotype\t")
+    for marker in markers:
+        f.write(marker + "\t")
+    for individual in order:
+        f.write("\n" + individual + "\t")
+        for i in range(len(markers)):
+            f.write(allele_dict[individual][i]+"\t")
+
+
+
+
+
+if __name__ == "__main__":
+    #replace the file names here and run the script
+    output("filename")
+    reorder("filename")
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