Spaces:
Running
Running
Arts-of-coding
commited on
Update dash_plotly_QC_scRNA.py
Browse files- dash_plotly_QC_scRNA.py +9 -8
dash_plotly_QC_scRNA.py
CHANGED
@@ -374,19 +374,20 @@ def update_graph_and_pie_chart(batch_chosen, s_chosen, g2m_chosen, condition1_ch
|
|
374 |
total_count = len(dff)
|
375 |
category_counts = category_counts.with_columns((pl.col("count") / total_count * 100).alias("normalized_count"))
|
376 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
377 |
# Calculate the mean expression
|
378 |
round_precision = 2
|
379 |
category_counts = dff.group_by(condition1_chosen).agg(pl.col(condition1_chosen).count().alias("count"))
|
380 |
category_sums = dff.group_by(condition1_chosen).agg(pl.col(condition1_chosen).sum().alias("sum"))
|
381 |
total_count = len(dff)
|
382 |
category_means = category_sums.select((pl.col("sum") / total_count).round(round_precision).alias("mean"))
|
383 |
-
|
384 |
-
# Display the result
|
385 |
-
labels = category_counts["batch"].to_list()
|
386 |
-
values = category_counts["normalized_count"].to_list()
|
387 |
-
|
388 |
-
total_cells = total_count # Calculate total number of cells
|
389 |
-
pie_title = f'Percentage of Total Cells: {total_cells}' # Include total cells in the title
|
390 |
|
391 |
fig_pie = px.pie(names=labels, values=values, title=pie_title,template="seaborn")
|
392 |
|
@@ -436,7 +437,7 @@ def update_graph_and_pie_chart(batch_chosen, s_chosen, g2m_chosen, condition1_ch
|
|
436 |
#labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
|
437 |
hover_name='batch',template="seaborn")
|
438 |
|
439 |
-
fig_scatter_12 = px.scatter(data_frame=dff, x=condition1_chosen, y=condition2_chosen, size=
|
440 |
#labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
|
441 |
hover_name='batch',template="seaborn")
|
442 |
|
|
|
374 |
total_count = len(dff)
|
375 |
category_counts = category_counts.with_columns((pl.col("count") / total_count * 100).alias("normalized_count"))
|
376 |
|
377 |
+
# Display the result
|
378 |
+
labels = category_counts["batch"].to_list()
|
379 |
+
values = category_counts["normalized_count"].to_list()
|
380 |
+
|
381 |
+
total_cells = total_count # Calculate total number of cells
|
382 |
+
pie_title = f'Percentage of Total Cells: {total_cells}' # Include total cells in the title
|
383 |
+
|
384 |
# Calculate the mean expression
|
385 |
round_precision = 2
|
386 |
category_counts = dff.group_by(condition1_chosen).agg(pl.col(condition1_chosen).count().alias("count"))
|
387 |
category_sums = dff.group_by(condition1_chosen).agg(pl.col(condition1_chosen).sum().alias("sum"))
|
388 |
total_count = len(dff)
|
389 |
category_means = category_sums.select((pl.col("sum") / total_count).round(round_precision).alias("mean"))
|
390 |
+
values_mean = category_counts["mean"].to_list()
|
|
|
|
|
|
|
|
|
|
|
|
|
391 |
|
392 |
fig_pie = px.pie(names=labels, values=values, title=pie_title,template="seaborn")
|
393 |
|
|
|
437 |
#labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
|
438 |
hover_name='batch',template="seaborn")
|
439 |
|
440 |
+
fig_scatter_12 = px.scatter(data_frame=dff, x=condition1_chosen, y=condition2_chosen, size=values_mean,
|
441 |
#labels={'X_umap-0': 'umap1' , 'X_umap-1': 'umap2'},
|
442 |
hover_name='batch',template="seaborn")
|
443 |
|