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Update dash_plotly_QC_scRNA.py
Browse files- dash_plotly_QC_scRNA.py +1 -5
dash_plotly_QC_scRNA.py
CHANGED
@@ -394,14 +394,10 @@ def update_graph_and_pie_chart(batch_chosen, s_chosen, g2m_chosen, condition1_ch
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# Melt wide format DataFrame into long format
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# Specify batch column as string type and gene columns as float type
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#list_conds = ["batch"]
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#list_conds = list_conds.append(condition3_chosen)
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list_conds = condition3_chosen
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list_conds += ["batch"]
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dff_pre = dff.select(list_conds)
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#dff_pre = dff.select(["batch","Cdc45","Mcm2","Mcm5"])
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# Melt wide format DataFrame into long format
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dff_long = dff_pre.melt(id_vars="batch", variable_name="Gene", value_name="Expression")
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@@ -458,7 +454,7 @@ def update_graph_and_pie_chart(batch_chosen, s_chosen, g2m_chosen, condition1_ch
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#labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
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hover_name='batch',template="seaborn")
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fig_scatter_12 = px.scatter(data_frame=expression_means, x="
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#labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
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hover_name='batch',template="seaborn")
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# Melt wide format DataFrame into long format
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# Specify batch column as string type and gene columns as float type
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list_conds = condition3_chosen
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list_conds += ["batch"]
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dff_pre = dff.select(list_conds)
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# Melt wide format DataFrame into long format
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dff_long = dff_pre.melt(id_vars="batch", variable_name="Gene", value_name="Expression")
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#labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
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hover_name='batch',template="seaborn")
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+
fig_scatter_12 = px.scatter(data_frame=expression_means, x="Gene", y="Batch", color="Mean expression",
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#labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
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hover_name='batch',template="seaborn")
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