diff --git a/dashboard/data/bmg_plate.py b/dashboard/data/bmg_plate.py
index 82662408..e0e03216 100644
--- a/dashboard/data/bmg_plate.py
+++ b/dashboard/data/bmg_plate.py
@@ -5,12 +5,6 @@
from enum import Enum, auto
-class Mode(Enum):
- ACTIVATION = auto()
- INHIBITION = auto()
- ALL = auto()
-
-
PlateSummary = namedtuple(
"PlateSummary",
[
@@ -194,7 +188,7 @@ def parse_bmg_files(files: tuple[str, io.StringIO]) -> tuple[pd.DataFrame, np.nd
def calculate_activation_inhibition_zscore(
values: np.ndarray,
stats: dict,
- mode: Mode = Mode.ALL,
+ mode: str,
without_pos: bool = False,
) -> tuple[np.ndarray]:
"""
@@ -207,8 +201,7 @@ def calculate_activation_inhibition_zscore(
:return: activation, inhibition and z-score values
"""
activation, inhibition = None, None
- if mode == Mode.ACTIVATION or mode == Mode.ALL:
- # NOTE: for now `without_pos` is not used
+ if mode == "activation":
if without_pos:
activation = (values - stats["mean_neg"]) / (stats["mean_neg"]) * 100
else:
@@ -218,10 +211,10 @@ def calculate_activation_inhibition_zscore(
* 100
)
- if mode == Mode.INHIBITION or mode == Mode.ALL:
+ if mode == "inhibition":
inhibition = (
- 1 - ((values - stats["mean_pos"])) / (stats["mean_neg"] - stats["mean_pos"])
- ) * 100
+ (values - stats["mean_neg"]) / (stats["mean_pos"] - stats["mean_neg"]) * 100
+ )
z_score = (values - stats["mean_cmpd"]) / stats["std_cmpd"]
@@ -229,14 +222,17 @@ def calculate_activation_inhibition_zscore(
def get_activation_inhibition_zscore_dict(
- df_stats: pd.DataFrame, plate_values: np.ndarray, modes: dict[Mode]
+ df_stats: pd.DataFrame,
+ plate_values: np.ndarray,
+ mode: str,
+ without_pos: bool = False,
) -> dict[str, dict[str, float]]:
"""
Calculates activation and inhibition for each compound in the plates.
:param df_stats: dataframe with statistics for each plate
:param plate_values: array with values in the plate
- :param mode: list of modes to calculate activation and inhibition
+ :param mode: mode to calculate activation and inhibition
:return: dictionary with activation and inhibition values for each compound in the plate
"""
stats = {}
@@ -251,11 +247,8 @@ def get_activation_inhibition_zscore_dict(
act_inh_dict = {}
for (_, row_stats), v in zip(df_stats.iterrows(), plate_values):
- mode = (
- modes[row_stats["barcode"]] if row_stats["barcode"] in modes else Mode.ALL
- )
activation, inhibition, z_score = calculate_activation_inhibition_zscore(
- v[0], stats, mode=mode
+ v[0], stats, mode, without_pos
)
act_inh_dict[row_stats["barcode"]] = {
"activation": activation,
diff --git a/dashboard/data/combine.py b/dashboard/data/combine.py
index bbd7be75..610f6abb 100644
--- a/dashboard/data/combine.py
+++ b/dashboard/data/combine.py
@@ -3,7 +3,7 @@
import numpy as np
import pandas as pd
-from dashboard.data.bmg_plate import Mode, get_activation_inhibition_zscore_dict
+from dashboard.data.bmg_plate import get_activation_inhibition_zscore_dict
def values_array_to_column(
@@ -93,7 +93,8 @@ def combine_bmg_echo_data(
echo_df: pd.DataFrame,
df_stats: pd.DataFrame,
plate_values: np.ndarray,
- modes: dict[Mode] = None,
+ mode: str,
+ without_pos: bool = False,
) -> pd.DataFrame:
"""
Combine Echo data with activation and inhibition values.
@@ -101,15 +102,15 @@ def combine_bmg_echo_data(
:param echo_df: dataframe with Echo data
:param df_stats: dataframe containing statistics for each plate
:param plate_values: numpy array with activation and inhibition values - shape: (#plates, 2, 16, 24)
- :param modes: dictionary with modes for each plate
+ :param mode: mode to calculate activation and inhibition
:return: dataframe with Echo data and activation and inhibition values
"""
PLATE = "Destination Plate Barcode"
WELL = "Destination Well"
- if modes is None:
- modes = dict()
- act_inh_dict = get_activation_inhibition_zscore_dict(df_stats, plate_values, modes)
+ act_inh_dict = get_activation_inhibition_zscore_dict(
+ df_stats, plate_values, mode, without_pos
+ )
dfs = []
for barcode, values_dict in act_inh_dict.items():
activation_inhibition_df = get_activation_inhibition_zscore_df(
@@ -150,7 +151,7 @@ def split_compounds_controls(df: pd.DataFrame) -> tuple[pd.DataFrame]:
def aggregate_well_plate_stats(
- df: pd.DataFrame, assign_x_coords: bool = False
+ df: pd.DataFrame, key: str, assign_x_coords: bool = False
) -> tuple[pd.DataFrame]:
"""
Aggregates the statistics (mean and std) per plate needed for the plots.
@@ -163,25 +164,19 @@ def aggregate_well_plate_stats(
"""
PLATE = "Destination Plate Barcode"
- ACTIVATION = "% ACTIVATION"
- INHIBITION = "% INHIBITION"
Z_SCORE = "Z-SCORE"
stats_df = (
- df.groupby(PLATE)[[ACTIVATION, INHIBITION, Z_SCORE]]
+ df.groupby(PLATE)[[key, Z_SCORE]]
.agg(["mean", "std", "min", "max"])
.reset_index()
)
stats_df.columns = [
PLATE,
- f"{ACTIVATION}_mean",
- f"{ACTIVATION}_std",
- f"{ACTIVATION}_min",
- f"{ACTIVATION}_max",
- f"{INHIBITION}_mean",
- f"{INHIBITION}_std",
- f"{INHIBITION}_min",
- f"{INHIBITION}_max",
+ f"{key}_mean",
+ f"{key}_std",
+ f"{key}_min",
+ f"{key}_max",
f"{Z_SCORE}_mean",
f"{Z_SCORE}_std",
f"{Z_SCORE}_min",
@@ -189,7 +184,7 @@ def aggregate_well_plate_stats(
]
if assign_x_coords:
- for col in [ACTIVATION, INHIBITION, Z_SCORE]:
+ for col in [key, Z_SCORE]:
stats_df = stats_df.sort_values(by=f"{col}_mean") # sort by mean
stats_df[f"{col}_x"] = range(len(stats_df)) # get the x coordinates
diff --git a/dashboard/pages/components.py b/dashboard/pages/components.py
index 640f9a89..9d534c1e 100644
--- a/dashboard/pages/components.py
+++ b/dashboard/pages/components.py
@@ -22,6 +22,7 @@
dcc.Store(id="z-slider-value", storage_type="local"),
dcc.Store(id="report-data-correlation-plots", storage_type="local"),
dcc.Store(id="report-data-hit-validation-input", storage_type="local"),
+ dcc.Store(id="activation-inhibition-screening-options", storage_type="local"),
],
)
diff --git a/dashboard/pages/screening/callbacks.py b/dashboard/pages/screening/callbacks.py
index 15e837d3..878e5558 100644
--- a/dashboard/pages/screening/callbacks.py
+++ b/dashboard/pages/screening/callbacks.py
@@ -1,6 +1,7 @@
import base64
import functools
import io
+import json
import uuid
from datetime import datetime
import json
@@ -25,7 +26,6 @@
from dashboard.data.combine import (
aggregate_well_plate_stats,
combine_bmg_echo_data,
- reorder_bmg_echo_columns,
split_compounds_controls,
)
from dashboard.data.file_preprocessing.echo_files_parser import EchoFilesParser
@@ -41,6 +41,10 @@
plot_z_per_plate,
visualize_multiple_plates,
)
+from dashboard.visualization.text_tables import (
+ make_filter_radio_options,
+ make_summary_stage_datatable,
+)
# === STAGE 1 ===
@@ -288,12 +292,37 @@ def upload_echo_data(
)
+def on_additional_options_change(
+ key: str,
+ formula: str,
+) -> dict[str, str]:
+ """
+ Update the additional screening options dictionary
+
+ :param screening_feature: screening feature
+ :param formula: formula
+ :return: updated dictionary
+ """
+ disabled = key != "activation"
+ options_dict = {}
+ options_dict["key"] = key
+ options_dict["feature_column"] = "% " + key.upper()
+ options_dict["without_pos"] = formula
+ return options_dict, disabled
+
+
# === STAGE 5 ===
def on_summary_entry(
- current_stage: int, stored_uuid: str, z_slider: float, file_storage: FileStorage
-) -> tuple[pd.DataFrame, go.Figure, go.Figure, go.Figure]:
+ current_stage: int,
+ stored_uuid: str,
+ z_slider: float,
+ screening_options: dict,
+ file_storage: FileStorage,
+) -> tuple[
+ pd.DataFrame, go.Figure, go.Figure, float, float, float, float, str, html.Div
+]:
"""
Callback for the stage 5 entry
Loads the data from storage and prepares visualizations
@@ -320,37 +349,41 @@ def on_summary_entry(
bmg_df, bmg_vals, z_slider["z_slider_value"]
)
- echo_bmg_combined = combine_bmg_echo_data(echo_df, filtered_df, filtered_vals)
- drop_duplicates = (
- True # TODO: inform the user about it/allow for deciding what to do
+ echo_bmg_combined = combine_bmg_echo_data(
+ echo_df,
+ filtered_df,
+ filtered_vals,
+ screening_options["key"],
+ screening_options["without_pos"],
)
-
- if drop_duplicates:
- echo_bmg_combined = echo_bmg_combined.drop_duplicates()
+ echo_bmg_combined = echo_bmg_combined.drop_duplicates()
compounds_df, control_pos_df, control_neg_df = split_compounds_controls(
echo_bmg_combined
)
compounds_df = compounds_df.dropna()
-
- activation_min = round(compounds_df["% ACTIVATION"].min())
- activation_max = round(compounds_df["% ACTIVATION"].max())
- inhibition_min = round(compounds_df["% INHIBITION"].min())
- inhibition_max = round(compounds_df["% INHIBITION"].max())
-
file_storage.save_file(
f"{stored_uuid}_echo_bmg_combined_df.pq", compounds_df.to_parquet()
)
- cmpd_plate_stats_df = aggregate_well_plate_stats(compounds_df, assign_x_coords=True)
- pos_plate_stats_df = aggregate_well_plate_stats(control_pos_df)
- neg_plate_stats_df = aggregate_well_plate_stats(control_neg_df)
+ cmpd_plate_stats_df = aggregate_well_plate_stats(
+ compounds_df, screening_options["feature_column"], assign_x_coords=True
+ )
+ pos_plate_stats_df = aggregate_well_plate_stats(
+ control_pos_df, screening_options["feature_column"]
+ )
+ neg_plate_stats_df = aggregate_well_plate_stats(
+ control_neg_df, screening_options["feature_column"]
+ )
plate_stats_dfs = [cmpd_plate_stats_df, pos_plate_stats_df, neg_plate_stats_df]
file_storage.save_file(
f"{stored_uuid}_plate_stats_df.pq", cmpd_plate_stats_df.to_parquet()
)
+ feature_min = round(compounds_df[screening_options["feature_column"]].min())
+ feature_max = round(compounds_df[screening_options["feature_column"]].max())
+
fig_z_score = plot_activation_inhibition_zscore(
compounds_df,
plate_stats_dfs,
@@ -358,51 +391,36 @@ def on_summary_entry(
(-3, 3), # z-score min and max
)
- fig_activation = plot_activation_inhibition_zscore(
+ fig_feature = plot_activation_inhibition_zscore(
compounds_df,
plate_stats_dfs,
- "% ACTIVATION",
- (activation_min, activation_max),
+ screening_options["feature_column"],
+ (feature_min, feature_max),
)
- fig_inhibition = plot_activation_inhibition_zscore(
- compounds_df,
- plate_stats_dfs,
- "% INHIBITION",
- (inhibition_min, inhibition_max),
+ compounds_url_df = eos_to_ecbd_link(compounds_df)
+ summary_stage_datatable = make_summary_stage_datatable(
+ compounds_url_df, screening_options["feature_column"]
)
- compounds_url_df = eos_to_ecbd_link(compounds_df)
+ radio_options = make_filter_radio_options(screening_options["key"])
report_data = {
"fig_z_score": fig_z_score.to_html(full_html=False, include_plotlyjs="cdn"),
- "fig_activation": fig_activation.to_html(
- full_html=False, include_plotlyjs="cdn"
- ),
- "fig_inhibition": fig_inhibition.to_html(
- full_html=False, include_plotlyjs="cdn"
- ),
+ "fig_feature": fig_feature.to_html(full_html=False, include_plotlyjs="cdn"),
}
return (
- compounds_url_df.to_dict("records"),
+ summary_stage_datatable,
fig_z_score,
- fig_activation,
- fig_inhibition,
+ fig_feature,
-3, # z_score_min,
3, # z_score_max,
- activation_min,
- activation_max,
- inhibition_min,
- inhibition_max,
- # NOTE: this will be cleared in the next PR (ACT/INH into one)
- False,
- False,
- False,
- False,
- False,
- False,
+ feature_min,
+ feature_max,
f"number of compounds: {len(compounds_df)}",
+ f"{screening_options['feature_column']} range:",
+ radio_options,
report_data,
)
@@ -411,10 +429,8 @@ def on_filter_radio_or_range_update(
key: str,
z_score_min: float,
z_score_max: float,
- activation_min: float,
- activation_max: float,
- inhibition_min: float,
- inhibition_max: float,
+ feature_min: float,
+ feature_max: float,
) -> dict:
"""
Callback for the filter radio button update
@@ -422,10 +438,8 @@ def on_filter_radio_or_range_update(
:param key: key to filter by
:param z_score_min: min z-score value
:param z_score_max: max z-score value
- :param activation_min: min activation value
- :param activation_max: max activation value
- :param inhibition_min: min inhibition value
- :param inhibition_max: max inhibition value
+ :param feature_min: min feature value
+ :param feature_max: max feature value
:return: dictionary storing the ranges of interest
"""
@@ -434,13 +448,9 @@ def on_filter_radio_or_range_update(
if key == "z_score":
report_data_csv["key_min"] = z_score_min
report_data_csv["key_max"] = z_score_max
- elif key == "activation":
- report_data_csv["key_min"] = activation_min
- report_data_csv["key_max"] = activation_max
- elif key == "inhibition":
- report_data_csv["key_min"] = inhibition_min
- report_data_csv["key_max"] = inhibition_max
-
+ elif key == "activation" or key == "inhibition":
+ report_data_csv["key_min"] = feature_min
+ report_data_csv["key_max"] = feature_max
return report_data_csv
@@ -449,8 +459,8 @@ def on_range_update(
max_value: float,
figure: go.Figure,
stored_uuid: str,
+ key: dict,
file_storage: FileStorage,
- key: str,
) -> go.Figure:
"""
Callback for the z-score range update button
@@ -464,8 +474,10 @@ def on_range_update(
:param key: key to filter by
:return: updated figure
"""
+ if key != "Z-SCORE":
+ key = key["feature_column"]
- if max_value is None or max_value is None or max_value < min_value:
+ if min_value is None or max_value is None or max_value < min_value:
return figure
new_figure = go.Figure(figure)
@@ -509,6 +521,7 @@ def on_range_update(
x=outside_range_df[f"{key}_x"],
y=outside_range_df[key],
customdata=np.stack((outside_range_df[PLATE], outside_range_df[WELL]), axis=-1),
+ text=outside_range_df["EOS"],
selector=dict(name="COMPOUNDS OUTSIDE"),
)
@@ -591,7 +604,6 @@ def on_report_generate_button_click(
report_data_second_stage: dict,
report_data_third_stage: dict,
report_data_screening_summary_plots: dict,
- file_storage: FileStorage,
):
filename = f"screening_report_{datetime.now().strftime('%Y-%m-%d')}.html"
report_data_second_stage.update(report_data_third_stage)
@@ -613,7 +625,6 @@ def on_json_generate_button_click(
report_data_second_stage: dict,
report_data_third_stage: dict,
report_data_csv: dict,
- file_storage: FileStorage,
):
filename = f"screening_settings_{datetime.now().strftime('%Y-%m-%d')}.json"
process_settings = read_stages_stats(
@@ -682,29 +693,30 @@ def register_callbacks(elements, file_storage):
)(functools.partial(upload_echo_data, file_storage=file_storage))
callback(
- Output("echo-bmg-combined", "data"),
+ Output("activation-inhibition-screening-options", "data"),
+ Output("activation-formula-dropdown", "disabled"),
+ Input("screening-feature-dropdown", "value"),
+ Input("activation-formula-dropdown", "value"),
+ )(on_additional_options_change)
+
+ callback(
+ Output("compounds-data-table", "children"),
Output("z-score-plot", "figure"),
- Output("activation-plot", "figure"),
- Output("inhibition-plot", "figure"),
+ Output("feature-plot", "figure"),
Output("z-score-min-input", "value"),
Output("z-score-max-input", "value"),
- Output("activation-min-input", "value"),
- Output("activation-max-input", "value"),
- Output("inhibition-min-input", "value"),
- Output("inhibition-max-input", "value"),
- Output("z-score-min-input", "disabled"),
- Output("z-score-max-input", "disabled"),
- Output("activation-min-input", "disabled"),
- Output("activation-max-input", "disabled"),
- Output("inhibition-min-input", "disabled"),
- Output("inhibition-max-input", "disabled"),
+ Output("feature-min-input", "value"),
+ Output("feature-max-input", "value"),
Output("compounds-data-subtitle", "children"),
+ Output("tab-feature-header", "children"),
+ Output("filter-radio", "options"),
Output("report-data-screening-summary-plots", "data"),
Input(elements["STAGES_STORE"], "data"),
State("user-uuid", "data"),
State("z-slider-value", "data"),
+ State("activation-inhibition-screening-options", "data"),
)(functools.partial(on_summary_entry, file_storage=file_storage))
-
+ # Z-SCORE
callback(
Output("z-score-plot", "figure", allow_duplicate=True),
Input("z-score-min-input", "value"),
@@ -712,33 +724,25 @@ def register_callbacks(elements, file_storage):
State("z-score-plot", "figure"),
State("user-uuid", "data"),
prevent_initial_call=True,
- )(functools.partial(on_range_update, file_storage=file_storage, key="Z-SCORE"))
- callback(
- Output("activation-plot", "figure", allow_duplicate=True),
- Input("activation-min-input", "value"),
- Input("activation-max-input", "value"),
- State("activation-plot", "figure"),
- State("user-uuid", "data"),
- prevent_initial_call=True,
- )(functools.partial(on_range_update, file_storage=file_storage, key="% ACTIVATION"))
+ )(functools.partial(on_range_update, key="Z-SCORE", file_storage=file_storage))
+ # ACTIVATION/INHIBITION
callback(
- Output("inhibition-plot", "figure", allow_duplicate=True),
- Input("inhibition-min-input", "value"),
- Input("inhibition-max-input", "value"),
- State("inhibition-plot", "figure"),
+ Output("feature-plot", "figure", allow_duplicate=True),
+ Input("feature-min-input", "value"),
+ Input("feature-max-input", "value"),
+ State("feature-plot", "figure"),
State("user-uuid", "data"),
+ State("activation-inhibition-screening-options", "data"),
prevent_initial_call=True,
- )(functools.partial(on_range_update, file_storage=file_storage, key="% INHIBITION"))
+ )(functools.partial(on_range_update, file_storage=file_storage))
callback(
Output("report-data-csv", "data"),
Input("filter-radio", "value"),
Input("z-score-min-input", "value"),
Input("z-score-max-input", "value"),
- Input("activation-min-input", "value"),
- Input("activation-max-input", "value"),
- Input("inhibition-min-input", "value"),
- Input("inhibition-max-input", "value"),
- )(functools.partial(on_filter_radio_or_range_update))
+ Input("feature-min-input", "value"),
+ Input("feature-max-input", "value"),
+ )(on_filter_radio_or_range_update)
callback(
Output("download-echo-bmg-combined", "data"),
Input("save-results-button", "n_clicks"),
@@ -760,7 +764,7 @@ def register_callbacks(elements, file_storage):
State("report-data-third-stage", "data"),
State("report-data-screening-summary-plots", "data"),
prevent_initial_call=True,
- )(functools.partial(on_report_generate_button_click, file_storage=file_storage))
+ )(on_report_generate_button_click)
callback(
Output("download-json-settings-screening", "data"),
Input("generate-json-button", "n_clicks"),
@@ -768,4 +772,4 @@ def register_callbacks(elements, file_storage):
State("report-data-third-stage", "data"),
State("report-data-csv", "data"),
prevent_initial_call=True,
- )(functools.partial(on_json_generate_button_click, file_storage=file_storage))
+ )(on_json_generate_button_click)
diff --git a/dashboard/pages/screening/report/report.html b/dashboard/pages/screening/report/report.html
index c2edc2e1..817dfa76 100644
--- a/dashboard/pages/screening/report/report.html
+++ b/dashboard/pages/screening/report/report.html
@@ -75,10 +75,7 @@
{{fig_z_score|safe}}
- {{fig_activation|safe}}
-
-
- {{fig_inhibition|safe}}
+ {{fig_feature|safe}}
diff --git a/dashboard/pages/screening/stages/s4_echo_input.py b/dashboard/pages/screening/stages/s4_echo_input.py
index 4da4cd4b..f783f7b1 100644
--- a/dashboard/pages/screening/stages/s4_echo_input.py
+++ b/dashboard/pages/screening/stages/s4_echo_input.py
@@ -1,4 +1,4 @@
-from dash import html, dcc
+from dash import dcc, html
ECHO_DESC = """
ECHO files in ".csv" format should have [DETAILS] and (if there are exceptions in the file) [EXCEPTIONS] tags
@@ -60,6 +60,82 @@
],
className="grid-2-1",
),
+ html.Div(
+ children=[
+ html.Div(
+ children=[
+ html.Div(
+ children=[
+ html.H5("Additional options "),
+ html.Div(
+ children=[
+ html.Div(
+ className="row",
+ children=[
+ html.Div(
+ [
+ html.Span("Screening feature:"),
+ html.Div(
+ children=[
+ dcc.Dropdown(
+ options=[
+ {
+ "label": "% ACTIVATION",
+ "value": "activation",
+ },
+ {
+ "label": "% INHIBITION",
+ "value": "inhibition",
+ },
+ ],
+ value="activation",
+ id="screening-feature-dropdown",
+ clearable=False,
+ ),
+ ],
+ ),
+ ],
+ className="col",
+ ),
+ html.Div(
+ [
+ html.Span(
+ "Activation formula:"
+ ),
+ html.Div(
+ children=[
+ dcc.Dropdown(
+ options=[
+ {
+ "label": "((x - μn)/(μp - μn)) * 100%",
+ "value": False,
+ },
+ {
+ "label": "(x - μn)/μn * 100%",
+ "value": True,
+ },
+ ],
+ value=False,
+ id="activation-formula-dropdown",
+ clearable=False,
+ ),
+ ],
+ ),
+ ],
+ className="col",
+ ),
+ ],
+ ),
+ ],
+ ),
+ ],
+ ),
+ ],
+ ),
+ html.Div(),
+ ],
+ className="grid-2-1",
+ ),
html.Div(
id="echo-filenames",
),
diff --git a/dashboard/pages/screening/stages/s5_summary.py b/dashboard/pages/screening/stages/s5_summary.py
index 258fe5e1..84219be3 100644
--- a/dashboard/pages/screening/stages/s5_summary.py
+++ b/dashboard/pages/screening/stages/s5_summary.py
@@ -2,280 +2,114 @@
from dash import dash_table, dcc, html
from dash.dash_table.Format import Format, Scheme
-PRECISION = 5
-ACT_INH_ZSCORE_DATATABLE = dash_table.DataTable(
- id="echo-bmg-combined",
- columns=[
- dict(id="EOS", name="ID", type="text", presentation="markdown"),
- dict(id="Destination Plate Barcode", name="Plate Barcode"),
- dict(id="Destination Well", name="Well"),
- dict(
- id="% ACTIVATION",
- name=" % ACTIVATION",
- type="numeric",
- format=Format(precision=PRECISION, scheme=Scheme.fixed),
- ),
- dict(
- id="% INHIBITION",
- name=" % INHIBITION",
- type="numeric",
- format=Format(precision=PRECISION, scheme=Scheme.fixed),
- ),
- dict(
- id="Z-SCORE",
- name=" Z-SCORE",
- type="numeric",
- format=Format(precision=PRECISION, scheme=Scheme.fixed),
- ),
- ],
- style_table={"overflowX": "auto", "overflowY": "auto"},
- style_data={
- "padding-left": "10px",
- "padding-right": "10px",
- "width": "70px",
- "autosize": {"type": "fit", "resize": True},
- "overflow": "hidden",
- },
- style_cell={
- "font-family": "sans-serif",
- "font-size": "12px",
- },
- style_header={
- "backgroundColor": "rgb(230, 230, 230)",
- "fontWeight": "bold",
- },
- style_data_conditional=[
- {
- "if": {"row_index": "odd"},
- "backgroundColor": "rgb(248, 248, 248)",
- },
- ],
- filter_action="native",
- filter_options={"case": "insensitive"},
- sort_action="native",
- column_selectable=False,
- page_size=15,
-)
-
-
-ACT_INH_ZSCORE_TABS = dcc.Tabs(
- id="summary-tabs",
+SUMMARY_STAGE = html.Div(
+ id="summary_stage",
+ className="container",
children=[
- dcc.Tab(
- label="Z-Score",
+ html.Div(
+ className="mb-5 mt-4",
children=[
- html.Div(
- className="my-4",
- children=[
- html.H5("Z-Score range:"),
- html.Div(
- className="row mb-3",
- children=[
- html.Div(
- className="col-md-6 mt-1",
- children=[
- html.Div(
- [
- html.Div(
- className="row",
- children=[
- html.Div(
- className="col",
- children=[
- html.Label(
- "minimum value:"
- ),
- dcc.Input(
- placeholder="min value",
- type="number",
- id="z-score-min-input",
- className="stats-input",
- disabled=True,
- ),
- ],
- ),
- html.Div(
- className="col",
- children=[
- html.Label(
- "maximum value:"
- ),
- dcc.Input(
- placeholder="max value",
- type="number",
- id="z-score-max-input",
- className="stats-input",
- disabled=True,
- ),
- ],
- ),
- ],
- )
- ],
- )
- ],
- ),
- ],
- ),
- html.Div(
- children=[
- dcc.Loading(
- id="loading-z-score-plot",
- children=[
- dcc.Graph(
- id="z-score-plot",
- figure={},
- ),
- ],
- type="circle",
- ),
- ],
- ),
- ],
+ html.H5("Filter results:"),
+ html.H6(
+ "The compounds in the csv report will be ones outside the range of the selected filter."
+ ),
+ dcc.RadioItems(
+ [],
+ value="no_filter",
+ style={"display": "flex"},
+ id="filter-radio",
),
],
),
- dcc.Tab(
- label="Activation",
+ dcc.Tabs(
+ id="summary-tabs",
children=[
- html.Div(
- className="my-4",
+ dcc.Tab(
+ label="Z-Score",
children=[
- html.H5("Activation range:"),
html.Div(
- className="row mb-3",
+ className="my-4",
children=[
+ html.H5("Z-Score range:"),
html.Div(
- className="col-md-6 mt-1",
+ className="row mb-3",
children=[
html.Div(
- [
- html.Div(
- className="row",
- children=[
- html.Div(
- className="col",
- children=[
- html.Label(
- "minimum value:"
- ),
- dcc.Input(
- placeholder="min value",
- type="number",
- id="activation-min-input",
- className="stats-input",
- disabled=True,
- ),
- ],
- ),
- html.Div(
- className="col",
- children=[
- html.Label(
- "maximum value:"
- ),
- dcc.Input(
- placeholder="max value",
- type="number",
- id="activation-max-input",
- className="stats-input",
- disabled=True,
- ),
- ],
- ),
- ],
- )
+ className="col mt-1",
+ children=[
+ html.Label("minimum value:"),
+ dcc.Input(
+ placeholder="min value",
+ type="number",
+ id="z-score-min-input",
+ className="stats-input",
+ ),
+ ],
+ ),
+ html.Div(
+ className="col mt-1",
+ children=[
+ html.Label("maximum value:"),
+ dcc.Input(
+ placeholder="max value",
+ type="number",
+ id="z-score-max-input",
+ className="stats-input",
+ ),
],
- )
- ],
- ),
- ],
- ),
- html.Div(
- children=[
- dcc.Loading(
- id="loading-activation-plot",
- children=[
- dcc.Graph(
- id="activation-plot",
- figure={},
),
],
- type="circle",
+ ),
+ dcc.Graph(
+ id="z-score-plot",
+ figure={},
),
],
),
],
),
- ],
- ),
- dcc.Tab(
- label="Inhibition",
- children=[
- html.Div(
- className="my-4",
+ dcc.Tab(
+ label="Activation/Inhibition",
children=[
- html.H5("Inhibition range:"),
html.Div(
- className="row mb-3",
+ className="my-4",
children=[
+ html.H5(
+ "Activation/Inhibition range:",
+ id="tab-feature-header",
+ ),
html.Div(
- className="col-md-6 mt-1",
+ className="row mb-3",
children=[
html.Div(
- [
- html.Div(
- className="row",
- children=[
- html.Div(
- className="col",
- children=[
- html.Label(
- "minimum value:"
- ),
- dcc.Input(
- placeholder="min value",
- type="number",
- id="inhibition-min-input",
- className="stats-input",
- disabled=True,
- ),
- ],
- ),
- html.Div(
- className="col",
- children=[
- html.Label(
- "maximum value:"
- ),
- dcc.Input(
- placeholder="max value",
- type="number",
- id="inhibition-max-input",
- className="stats-input",
- disabled=True,
- ),
- ],
- ),
- ],
- )
+ className="col mt-1",
+ children=[
+ html.Label("minimum value:"),
+ dcc.Input(
+ placeholder="min value",
+ type="number",
+ id="feature-min-input",
+ className="stats-input",
+ ),
+ ],
+ ),
+ html.Div(
+ className="col mt-1",
+ children=[
+ html.Label("maximum value:"),
+ dcc.Input(
+ placeholder="max value",
+ type="number",
+ id="feature-max-input",
+ className="stats-input",
+ ),
],
- )
- ],
- ),
- ],
- ),
- html.Div(
- children=[
- dcc.Loading(
- id="loading-inhibition-plot",
- children=[
- dcc.Graph(
- id="inhibition-plot",
- figure={},
),
],
- type="circle",
+ ),
+ dcc.Graph(
+ id="feature-plot",
+ figure={},
),
],
),
@@ -283,49 +117,6 @@
),
],
),
- ],
-)
-
-
-radio_values = ["Retain all", "Z-Score", "Activation", "Inhibition"]
-radio_codes = ["no_filter", "z_score", "activation", "inhibition"]
-radio_options = []
-
-for i, j in zip(radio_values, radio_codes):
- radio_options.append(
- {
- "label": html.Div(
- i,
- style={
- "display": "inline",
- "padding-left": "0.5rem",
- "padding-right": "2rem",
- },
- ),
- "value": j,
- }
- )
-
-SUMMARY_STAGE = html.Div(
- id="summary_stage",
- className="container",
- children=[
- html.Div(
- className="mb-5 mt-4",
- children=[
- html.H5("Filter results:"),
- html.H6(
- "The compounds in the csv report will be ones outside the range of the selected filter."
- ),
- dcc.RadioItems(
- radio_options,
- "no_filter",
- style={"display": "flex"},
- id="filter-radio",
- ),
- ],
- ),
- ACT_INH_ZSCORE_TABS,
html.Div(
className="my-4",
children=[
@@ -350,7 +141,8 @@
),
html.Div(
className="overflow-auto mx-2 border border-3 rounded shadow bg-body-tertiary",
- children=[ACT_INH_ZSCORE_DATATABLE],
+ children=[],
+ id="compounds-data-table",
),
],
),
diff --git a/dashboard/visualization/text_tables.py b/dashboard/visualization/text_tables.py
index ed18f536..4e333221 100644
--- a/dashboard/visualization/text_tables.py
+++ b/dashboard/visualization/text_tables.py
@@ -3,6 +3,102 @@
from dash.dash_table.Format import Format, Scheme
from sklearn.decomposition import PCA
+PRECISION = 5
+
+
+def make_filter_radio_options(key: str):
+ """
+ Creates the options for the filter radio buttons.
+
+ :param key: key for the filter
+ :return: list of dictionaries with the options for the filter radio buttons
+ """
+ radio_values = ["No filter (retain all)", "Z-Score", "Activation", "Inhibition"]
+ radio_codes = ["no_filter", "z_score", "activation", "inhibition"]
+ radio_codes_to_be_created = ["no_filter", "z_score", key]
+ radio_options = []
+
+ for i, j in zip(radio_values, radio_codes):
+ if j in radio_codes_to_be_created:
+ radio_options.append(
+ {
+ "label": html.Div(
+ i,
+ style={
+ "display": "inline",
+ "padding-left": "0.5rem",
+ "padding-right": "2rem",
+ },
+ ),
+ "value": j,
+ }
+ )
+
+ return radio_options
+
+
+def make_summary_stage_datatable(df: pd.DataFrame, feature: str):
+ """
+ Creates the datatable for the summary stage.
+
+ :param df: dataframe with the data
+ :param feature: feature to be displayed (% ACTIVATION,% INHIBITION)
+ :return: datatable with the data
+ """
+ data = df.to_dict("records")
+ feature_dict = dict(
+ id=feature,
+ name=feature,
+ type="numeric",
+ format=Format(precision=PRECISION, scheme=Scheme.fixed),
+ )
+
+ ACT_INH_DATATABLE = dash_table.DataTable(
+ id="compounds-data-table",
+ data=data,
+ columns=[
+ dict(id="EOS", name="ID", type="text", presentation="markdown"),
+ dict(id="Destination Plate Barcode", name="Plate Barcode"),
+ dict(id="Destination Well", name="Well"),
+ feature_dict,
+ dict(
+ id="Z-SCORE",
+ name=" Z-SCORE",
+ type="numeric",
+ format=Format(precision=PRECISION, scheme=Scheme.fixed),
+ ),
+ ],
+ style_table={"overflowX": "auto", "overflowY": "auto"},
+ style_data={
+ "padding-left": "10px",
+ "padding-right": "10px",
+ "width": "70px",
+ "autosize": {"type": "fit", "resize": True},
+ "overflow": "hidden",
+ },
+ style_cell={
+ "font-family": "sans-serif",
+ "font-size": "12px",
+ },
+ style_header={
+ "backgroundColor": "rgb(230, 230, 230)",
+ "fontWeight": "bold",
+ },
+ style_data_conditional=[
+ {
+ "if": {"row_index": "odd"},
+ "backgroundColor": "rgb(248, 248, 248)",
+ },
+ ],
+ filter_action="native",
+ filter_options={"case": "insensitive"},
+ sort_action="native",
+ column_selectable=False,
+ page_size=15,
+ )
+
+ return ACT_INH_DATATABLE
+
def table_from_df(df: pd.DataFrame, table_id: str) -> html.Div:
"""
diff --git a/tests/bmg_plate_test.py b/tests/bmg_plate_test.py
index 61a942d1..89e3bfae 100644
--- a/tests/bmg_plate_test.py
+++ b/tests/bmg_plate_test.py
@@ -4,7 +4,6 @@
import pandas as pd
from dashboard.data.bmg_plate import (
- Mode,
calculate_activation_inhibition_zscore,
filter_low_quality_plates,
get_activation_inhibition_zscore_dict,
@@ -50,19 +49,19 @@ def test_calculate_activation_inhibition_zscore(stats_for_all):
values = np.array([5, 3, 3])
activation, inhibition, z_score = calculate_activation_inhibition_zscore(
- values, stats_for_all
+ values, stats_for_all, "activation", False
)
assert (
round(activation[2], 2) == -199.25
- and round(inhibition[1], 2) == -199.25
and round(z_score[0], 2) == -82.92
+ and inhibition is None
)
def test_get_activation_inhibition_zscore_dict(df_stats):
values = np.full((2, 2, 16, 24), 2)
values[1] = 1.5
- z_dict = get_activation_inhibition_zscore_dict(df_stats, values, modes=dict())
+ z_dict = get_activation_inhibition_zscore_dict(df_stats, values, "activation")
assert np.array_equal(z_dict["1234"]["z_score"], np.full((16, 24), 1.0))
diff --git a/tests/combine_test.py b/tests/combine_test.py
index a988d143..228e76c3 100644
--- a/tests/combine_test.py
+++ b/tests/combine_test.py
@@ -6,7 +6,6 @@
split_compounds_controls,
combine_bmg_echo_data,
)
-from dashboard.data.bmg_plate import Mode
def test_values_array_to_column():
@@ -69,8 +68,7 @@ def test_combine_bmg_echo_data(df_stats):
r"0(?!$)", "", regex=True
)
plate_values = np.random.rand(1, 2, 16, 24)
- modes = {"1234": Mode.ACTIVATION}
- combined_df = combine_bmg_echo_data(echo_df, df_stats, plate_values, modes)
+ combined_df = combine_bmg_echo_data(echo_df, df_stats, plate_values, "activation")
assert len(combined_df) == 384
assert set(combined_df.columns) == set(echo_data.keys()) | {