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HI I AM TRYING TO FIND THE CORRELATION OF THE MODULES OF MY WGCNA OBJECT WITH THE TRAITS OF MY METADATA , BUT I GET THE FOLLOWING ERROR, DO ANYONE KNOW HOW TO SOLVE IT? THANK YOU.
Yes I did update the sample and gene info following all the steps of the quick start tutorial up to the one wich gave me the error. I will upload a photo of the pyWGCNA_TCGA_PAAD.datExpr.obs dataframe and the sample info file so that you can explore the metadata I am using. Thank you for your time and answers.
oh, it's probably because you have a dash in your column name like "Cluster_0"
I will try to fix this problem but meanwhile, if you can change your column names to be dash-free, it will probably solve your problem for now
Thank you for catching that! I'll try to see how I can fix that :)
HI I AM TRYING TO FIND THE CORRELATION OF THE MODULES OF MY WGCNA OBJECT WITH THE TRAITS OF MY METADATA , BUT I GET THE FOLLOWING ERROR, DO ANYONE KNOW HOW TO SOLVE IT? THANK YOU.
pyWGCNA_TCGA_PAAD.analyseWGCNA()
Analysing WGCNA...
Calculating module trait relationship ...
Done..
Adding (signed) eigengene-based connectivity (module membership) ...
Done..
plotting module heatmap eigengene...
Done..
plotting module barplot eigengene...
ValueError Traceback (most recent call last)
Cell In[10], line 1
----> 1 pyWGCNA_TCGA_PAAD.analyseWGCNA()
File ~/miniconda3/envs/machine_learning/lib/python3.11/site-packages/PyWGCNA/wgcna.py:447, in WGCNA.analyseWGCNA(self, order, geneList, show)
445 print(f"{OKCYAN}plotting module barplot eigengene...{ENDC}")
446 for module in modules:
--> 447 self.barplotModuleEigenGene(module, metadata, colorBar=metadata[-1], show=True)
448 print("\tDone..\n")
450 if self.save:
File ~/miniconda3/envs/machine_learning/lib/python3.11/site-packages/PyWGCNA/wgcna.py:2946, in WGCNA.barplotModuleEigenGene(self, moduleName, metadata, combine, colorBar, show)
2944 df['all'] = df['all'].apply(lambda x: x[1:])
2945 cat = pd.DataFrame(pd.unique(df['all']), columns=['all'])
-> 2946 cat[metadata] = cat['all'].str.split('_', expand=True)
2947 ybar = df[['all', 'eigengeneExp']].groupby(['all']).mean()['eigengeneExp']
2948 ebar = df[['all', 'eigengeneExp']].groupby(['all']).std()['eigengeneExp']
File ~/miniconda3/envs/machine_learning/lib/python3.11/site-packages/pandas/core/frame.py:3968, in DataFrame.setitem(self, key, value)
3966 self._setitem_frame(key, value)
3967 elif isinstance(key, (Series, np.ndarray, list, Index)):
-> 3968 self._setitem_array(key, value)
3969 elif isinstance(value, DataFrame):
3970 self._set_item_frame_value(key, value)
...
402 else:
403 # Missing keys in columns are represented as -1
404 if len(columns.get_indexer_non_unique(key)[0]) != len(value.columns):
ValueError: Columns must be same length as key
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