Browse Source

Update SFS plotting function

tforest 10 months ago
parent
commit
44449033db
2 changed files with 28 additions and 13 deletions
  1. 6 3
      customgraphics.py
  2. 22 10
      sfs_tools.py

+ 6 - 3
customgraphics.py View File

@@ -200,14 +200,14 @@ def scatter(x, y, ylab=None, xlab=None, title=None):
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         plt.title(title)
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     plt.show()
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-def barplot(x=None, y=None, ylab=None, xlab=None, title=None):
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+def barplot(x=None, y=None, ylab=None, xlab=None, title=None, label=None, xticks = None, width=1):
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     if x:
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         x = list(x)
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         plt.xticks(x)
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-        plt.bar(x, y)
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+        plt.bar(x, y, width=width, label=label)
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     else:
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         x = list(range(len(y)))
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-        plt.bar(x, y)
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+        plt.bar(x, y, width=width, label=label)
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         plt.xticks(x)
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     if ylab:
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         plt.ylabel(ylab)
@@ -215,6 +215,9 @@ def barplot(x=None, y=None, ylab=None, xlab=None, title=None):
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         plt.xlabel(xlab)
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     if title:
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         plt.title(title)
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+    if xticks:
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+        plt.xticks(xticks)
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+    plt.legend()
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     plt.show()
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 def plot_chrom_continuity(vcf_entries, chr_id, x=None, y=None, outfile = None,

+ 22 - 10
sfs_tools.py View File

@@ -21,6 +21,7 @@ import gzip
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 import sys
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 import matplotlib.pyplot as plt
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 from frst import customgraphics
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+import numpy as np
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 def sfs_from_vcf(n, vcf_file, folded = True, diploid = True, phased = False, verbose = False,
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                  strip = False, count_ext = False):
@@ -192,7 +193,7 @@ def sfs_from_parsed_vcf(n, vcf_dict, folded = True, diploid = True, phased = Fal
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     return SFS_values, count_pluriall
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-def barplot_sfs(sfs,  xlab, ylab, folded=True, title = "Barplot", transformed = False, normalized = False):
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+def barplot_sfs(sfs,  xlab, ylab, folded=True, title = "Barplot", transformed = False, normalized = False, ploidy = 2):
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     sfs_val = []
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     n = len(sfs.values())
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     sum_sites = sum(list(sfs.values()))
@@ -222,7 +223,7 @@ def barplot_sfs(sfs,  xlab, ylab, folded=True, title = "Barplot", transformed =
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     #terminal case, same for folded or unfolded
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     if transformed:
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-        last_bin = list(sfs.values())[n-1] * n/2
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+        last_bin = list(sfs.values())[n-1] * n/ploidy
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     else:
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         last_bin = list(sfs.values())[n-1]
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     sfs_val[-1] = last_bin
@@ -235,22 +236,33 @@ def barplot_sfs(sfs,  xlab, ylab, folded=True, title = "Barplot", transformed =
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         #print(sum(sfs_val))
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     #build the plot
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-    title = title+" (n="+str(len(sfs_val))+") [folded="+str(folded)+"]"+" [transformed="+str(transformed)+"]"
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-    print("SFS =", sfs)
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     if folded:
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         xlab = "Minor allele frequency"
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+        n_title = n
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+    else:
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+        # the spectrum is n-1 long when unfolded
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+        n_title = n+1
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+    
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+    title = title+" (n="+str(n_title)+") [folded="+str(folded)+"]"+" [transformed="+str(transformed)+"]"
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+    print("SFS =", sfs)
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+
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+    X_axis = list(sfs.keys()) 
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+    
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+
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     if transformed:
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-        print("Transformed SFS ( n =",len(sfs_val), ") :", sfs_val)
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+        print("Transformed SFS ( n =",n_title, ") :", sfs_val)
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         #plt.axhline(y=1/n, color='r', linestyle='-')
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+        plt.bar([x+0.2 for x in list(sfs.keys())], [1/n]*n, color='r', linestyle='-', width = 0.4, label= "H0 Theoric constant")
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+
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     else:
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         if normalized:
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             # then plot a theoritical distribution as 1/i
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-            expected_y = [1/(2*x+1) for x in list(sfs.keys())]
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+            sum_expected = sum([(1/(i+1)) for i,x in enumerate(list(sfs.keys()))])
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+            expected_y = [(1/(i+1))/sum_expected for i,x in enumerate(list(sfs.keys()))]
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+            print(expected_y)
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+            plt.bar([x+0.2 for x in list(sfs.keys())], expected_y, color='r', linestyle='-', width = 0.4, label= "H0 Theoric constant")
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             print(sum(expected_y))
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-            #plt.plot([x for x in list(sfs.keys())], expected_y, color='r', linestyle='-')
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-            #print(expected_y)
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-            
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-    customgraphics.barplot(x = [x for x in list(sfs.keys())], y= sfs_val, xlab = xlab, ylab = ylab, title = title)
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+    customgraphics.barplot(x = [x-0.2 for x in X_axis], width=0.4, y= sfs_val, xlab = xlab, ylab = ylab, title = title, label = "H1 Observed spectrum", xticks =list(sfs.keys()) )
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     plt.show()
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 if __name__ == "__main__":