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Fixed some bugs in Manhattan plotting #47

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Fixed some bugs in Manhattan plotting #47

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29 changes: 15 additions & 14 deletions bioinfokit/visuz.py
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Original file line number Diff line number Diff line change
Expand Up @@ -577,15 +577,18 @@ def geneplot_mhat(df, markeridcol, chr, pv, gwasp, markernames, gfont, gstyle, a
if markeridcol is not None:
if markernames is not None and markernames is True:
for i in df[markeridcol].unique():
if df.loc[df[markeridcol] == i, pv].iloc[0] <= gwasp:
if gstyle == 1:
plt.text(df.loc[df[markeridcol] == i, 'ind'].iloc[0], df.loc[df[markeridcol] == i, 'tpval'].iloc[0],
str(i), fontsize=gfont)
elif gstyle == 2:
plt.annotate(i, xy=(df.loc[df[markeridcol] == i, 'ind'].iloc[0], df.loc[df[markeridcol] == i, 'tpval'].iloc[0]),
xycoords='data', xytext=(5, -15), textcoords='offset points', size=6,
bbox=dict(boxstyle="round", alpha=0.2),
arrowprops=dict(arrowstyle="wedge,tail_width=0.5", alpha=0.2, relpos=(0, 0)))
for j in range(len(df[chr].unique())):

@li-liwen li-liwen Apr 17, 2022

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This for-loop enables the annotator iterates all the chromosome, so that it won't only mark the first chromosome.

if df.loc[df[markeridcol] == i, pv].iloc[j] <= gwasp:
if gstyle == 1:
plt.text(df.loc[df[markeridcol] == i, 'ind'].iloc[j], df.loc[df[markeridcol] == i, 'tpval'].iloc[j],
str(i), fontsize=gfont)
elif gstyle == 2:
plt.annotate(i, xy=(df.loc[df[markeridcol] == i, 'ind'].iloc[j], df.loc[df[markeridcol] == i, 'tpval'].iloc[j]),
xycoords='data', xytext=(5, -15), textcoords='offset points', size=6,
bbox=dict(boxstyle="round", alpha=0.2),
arrowprops=dict(arrowstyle="wedge,tail_width=0.5", alpha=0.2, relpos=(0, 0)))


elif markernames is not None and isinstance(markernames, (tuple, list)):
for i in df[markeridcol].unique():
if i in markernames:
Expand Down Expand Up @@ -631,7 +634,7 @@ def mhat(df="dataframe", chr=None, pv=None, log_scale=True, color=None, dim=(6,4
df['tpval'] = df[pv]
# df = df.sort_values(chr)
# if the column contains numeric strings
df = df.loc[pd.to_numeric(df[chr], errors='coerce').sort_values().index]
df = df.loc[pd.to_numeric(df[chr], errors='ignore').sort_values().index]

@li-liwen li-liwen Apr 17, 2022

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'coerce' will produce nan if not convertible, while ignore will maintain the input. This change from makes the column still sortable even if it cannot be converted to numbers. If the column isn't sorted, it will result in color problem in the plot.

# add indices
df['ind'] = range(len(df))
df_group = df.groupby(chr)
Expand All @@ -657,14 +660,12 @@ def mhat(df="dataframe", chr=None, pv=None, log_scale=True, color=None, dim=(6,4
if theme == 'dark':
general.dark_bg()
fig, ax = plt.subplots(figsize=dim)
i = 0
for label, df1 in df.groupby(chr):
for i, (label, df1) in enumerate(df.groupby(chr)):
df1.plot(kind='scatter', x='ind', y='tpval', color=color_list[i], s=dotsize, alpha=valpha, ax=ax)
df1_max_ind = df1['ind'].iloc[-1]
df1_min_ind = df1['ind'].iloc[0]
xlabels.append(label)
xticks.append((df1_max_ind - (df1_max_ind - df1_min_ind) / 2))
i += 1

# add GWAS significant line
if gwas_sign_line is True:
Expand All @@ -681,7 +682,7 @@ def mhat(df="dataframe", chr=None, pv=None, log_scale=True, color=None, dim=(6,4
else:
ylm = np.arange(0, max(df['tpval']+1), 1)
ax.set_yticks(ylm)
ax.set_xticklabels(xlabels, rotation=ar)
ax.set_xticklabels(xlabels, fontsize=axtickfontsize, fontproperties=axtickfontname, rotation=ar)

@li-liwen li-liwen Apr 17, 2022

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This enables the caller to change font name and font size of tick labels, which is especially useful when the labels is in another language.

# ax.set_yticklabels(ylm, fontsize=axtickfontsize, fontname=axtickfontname, rotation=ar)
if axxlabel:
_x = axxlabel
Expand Down