Release v2.1.7

Dockerfile

@@ -1,24 +1,26 @@
-# Set the base image to anaconda python 3.8
-FROM continuumio/miniconda3
+# Set the base image to micromamba
+FROM mambaorg/micromamba
 
 # File Author / Maintainer
-# MAINTAINER Samuele Cancelleri
+LABEL org.opencontainers.image.authors="ManuelTgn, lucapinello"
 
-ENV SHELL bash
+# Set the variables for version control during installation
+ARG crispritz_version=2.6.6
+# TODO: update crisprme version to 2.1.7
+ARG crisprme_version=2.1.6
 
-#update conda channel with bioconda and conda-forge
-RUN conda config --add channels defaults 
-RUN conda config --add channels conda-forge
-RUN conda config --add channels bioconda
+# set the shell to bash
+ENV SHELL bash
+# set user as root
+USER root
 
-#update packages of the docker system
+#update packages of the docker image
 RUN apt-get update && apt-get install gsl-bin libgsl0-dev -y && apt-get install libgomp1 -y && apt-get clean
 RUN apt-get upgrade -y && apt-get clean
 RUN apt update
 RUN apt upgrade -y
 
-#Install crisprme package
-RUN conda install crispritz -y
-RUN conda install crisprme -y
-RUN conda update crispritz -y
-RUN conda update crisprme -y
+# Install crispritz & crisprme packages
+RUN micromamba install -y -n base -c conda-forge -c bioconda python=3.9 crispritz=$crispritz_version crisprme=$crisprme_version && micromamba clean --all --yes
+# Start the base environment
+ARG MAMBA_DOCKERFILE_ACTIVATE=1

LICENSE

@@ -1,2 +1,16 @@
-CRISRPme has a dual license. It is made available for free to academic researchers under the Affero License (https://www.gnu.org/licenses/agpl-3.0.en.html).
-If you plan to use the CRISRPme for-profit, you will need to purchase a license. Please contact [email protected] and [email protected] for more information.
+CRISPRme is distributed under a dual-license model:  
+
+1. Academic Use 
+    CRISPRme is freely available for academic research under the GNU Affero 
+    General Public License v3.0 (AGPL-3.0)
+    (https://www.gnu.org/licenses/agpl-3.0.en.html). 
+
+2. Commercial Use 
+    For-profit institutions or users intending to use CRISPRme for commercial 
+    purposes must acquire a commercial license. For inquiries and licensing 
+    details, please contact:
+        - Luca Pinello: [email protected]  
+        - Rosalba Giugno: [email protected]
+
+For more information on licensing terms and conditions, please reach out to the 
+contacts above.

PostProcess/CFDGraph.py

@@ -1,4 +1,4 @@
-'''
+"""
 Crea area graph per distribuzione del CFD. Per ogni valore di CFD (0-100) sull'asse X, indica sull'asse y il numero di target con quel
 valore di CFD, distinti in REF e VAR. In input prende il file .CDFGraph.txt
 TODO Modificare lo script in modo da aggiungere un dash Input, in modo che l'utente possa scrivere un sample da visualizzare, e un Button
@@ -13,10 +13,9 @@
         https://dash.plotly.com/dash-core-components/graph
         https://dash.plotly.com/interactive-graphing
 NOTE 127.0.0.1:8050 per aprire la pagina (o 0.0.0.0:8050)
-'''
+"""
 
-
-import plotly.graph_objects as go # or plotly.express as px
+import plotly.graph_objects as go  # or plotly.express as px
 
 # fig.add_trace( ... )
 # fig.update_layout( ... )
@@ -27,50 +26,73 @@
 from dash.exceptions import PreventUpdate
 import sys
 
+
 def createGraph(cfd_distribution, showLog):
-    fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
-    fig.add_trace(go.Scatter(x=list(range(101)), y=list(cfd_distribution['ref']), fill='tozeroy', name = 'Tagets in Reference',#fillcolor = 'yellow',
-                    #mode='none' # override default markers+lines
-                        ))
-    fig.add_trace(go.Scatter(x=list(range(101)), y=list(cfd_distribution['var']), fill='tozeroy',name = 'Targets in Enriched',
-                        #mode= 'none'
-                        ))
+    fig = go.Figure()  # or any Plotly Express function e.g. px.bar(...)
+    fig.add_trace(
+        go.Scatter(
+            x=list(range(101)),
+            y=list(cfd_distribution["ref"]),
+            fill="tozeroy",
+            name="Tagets in Reference",  # fillcolor = 'yellow',
+            # mode='none' # override default markers+lines
+        )
+    )
+    fig.add_trace(
+        go.Scatter(
+            x=list(range(101)),
+            y=list(cfd_distribution["var"]),
+            fill="tozeroy",
+            name="Targets in Enriched",
+            # mode= 'none'
+        )
+    )
     if showLog:
-        fig.update_layout(yaxis_type="log", xaxis_title="CFD Value",
-        yaxis_title="Number of Targets (log scale)", hovermode = 'x')
+        fig.update_layout(
+            yaxis_type="log",
+            xaxis_title="CFD Value",
+            yaxis_title="Number of Targets (log scale)",
+            hovermode="x",
+        )
     else:
-        fig.update_layout( xaxis_title="CFD Value",
-        yaxis_title="Number of Targets",hovermode = 'x')
+        fig.update_layout(
+            xaxis_title="CFD Value", yaxis_title="Number of Targets", hovermode="x"
+        )
     return fig
 
+
 import dash
 import dash_core_components as dcc
 import dash_html_components as html
 
+
 def CFDGraph(CFD_total_path):
     if CFD_total_path is None:
-        return ''
+        return ""
     final_list = []
-    final_list.append(html.P('Number of targets found in the Reference and Enriched Genome for each CFD Score value (0-100)'))
+    final_list.append(
+        html.P(
+            "Number of targets found in the Reference and Enriched Genome for each CFD Score value (0-100)"
+        )
+    )
     # final_list.append(
     #     dcc.Checklist(
     #         options = [
     #             {'label':'Log value for Number of Targets','value':'logval', 'disabled':False}
-    #         ], 
+    #         ],
     #         value = ['logval'],
     #         id = 'checklist-advanced',
-            
+
     #     ),
     # )
-    cfd_distribution = pd.read_csv(CFD_total_path, sep = '\t')
+    cfd_distribution = pd.read_csv(CFD_total_path, sep="\t")
     final_list.append(
         html.Div(
-            dcc.Graph(figure=createGraph(cfd_distribution,True), id = 'CFD-graph-id'),
-            id = 'div-CFD-graph'
+            dcc.Graph(figure=createGraph(cfd_distribution, True), id="CFD-graph-id"),
+            id="div-CFD-graph",
         )
     )
-    final_list.append(html.Div(id = 'selected-data'))
-
+    final_list.append(html.Div(id="selected-data"))
 
     final_list.append(html.Br())
     # import plotly.express as px
@@ -81,6 +103,7 @@ def CFDGraph(CFD_total_path):
     # final_list.append(dcc.Graph(figure = fig, id = 'graph-id2'))
     return final_list
 
+
 # @app.callback(
 #     Output('div-graph','children'),
 #     [Input('checklist-advanced', 'value')]
@@ -101,5 +124,5 @@ def CFDGraph(CFD_total_path):
 #     print(selectedData) #NOTE non funziona
 #     return ''
 
-if __name__ == '__main__':
-    CFDGraph(None)
+if __name__ == "__main__":
+    CFDGraph(None)