add GUI, switch to importlib, fix glycoDE error

bin/glycoworkGUI.py

@@ -0,0 +1,177 @@
+import os
+import sys
+import tkinter as tk
+from tkinter import simpledialog, filedialog, messagebox
+from glycowork.motif.draw import GlycoDraw, plot_glycans_excel
+from glycowork.motif.analysis import get_differential_expression
+
+
+# Function to get the resource path within the executable environment
+def resource_path(relative_path):
+    """ Get the absolute path to the resource, works for dev and PyInstaller """
+    try:
+        # PyInstaller creates a temp folder and stores path in _MEIPASS
+        base_path = sys._MEIPASS
+    except Exception:
+        base_path = os.path.abspath(".")
+
+    return os.path.join(base_path, relative_path)
+
+
+class GlycoDrawDialog(simpledialog.Dialog):
+    def body(self, master):
+        self.title("GlycoDraw Input")
+        tk.Label(master, text = "Glycan Sequence:").grid(row = 0)
+        self.sequence_entry = tk.Entry(master)
+        self.sequence_entry.grid(row = 0, column = 1)
+        return self.sequence_entry  # to put focus on the glycan sequence entry widget
+
+    def apply(self):
+        glycan_sequence = self.sequence_entry.get()
+        file_path = filedialog.asksaveasfilename(filetypes = [("PDF Image", "*.pdf")], defaultextension = ".pdf")
+        if file_path:  # ensuring the user didn't cancel the save dialog
+            self.result = glycan_sequence, file_path
+
+
+def openGlycoDrawDialog():
+    dialog_result = GlycoDrawDialog(app)
+    if dialog_result.result:
+        glycan_sequence, file_path = dialog_result.result
+        GlycoDraw(glycan_sequence, filepath = file_path)
+
+
+class GlycoDrawExcelDialog(simpledialog.Dialog):
+    def body(self, master):
+        self.title("GlycoDrawExcel Input")
+        tk.Label(master, text="Select CSV File:").grid(row = 0)
+
+        self.csv_entry = tk.Entry(master)
+        self.csv_entry.grid(row = 0, column = 1)
+        self.csv_button = tk.Button(master, text = "Browse...", command = self.browse_csv)
+        self.csv_button.grid(row = 0, column = 2)
+
+        tk.Label(master, text = "Output Folder:").grid(row = 1)
+        self.folder_entry = tk.Entry(master)
+        self.folder_entry.grid(row = 1, column = 1)
+        self.folder_button = tk.Button(master, text = "Browse...", command = self.browse_folder)
+        self.folder_button.grid(row = 1, column = 2)
+
+        return self.csv_entry  # to put focus on the csv file entry widget
+
+    def browse_csv(self):
+        file_path = filedialog.askopenfilename(filetypes = [("CSV Files", "*.csv")])
+        if file_path:
+            self.csv_entry.delete(0, tk.END)
+            self.csv_entry.insert(0, file_path)
+
+    def browse_folder(self):
+        folder_path = filedialog.askdirectory()
+        if folder_path:
+            self.folder_entry.delete(0, tk.END)
+            self.folder_entry.insert(0, folder_path)
+
+    def apply(self):
+        csv_file_path = self.csv_entry.get()
+        output_folder = self.folder_entry.get()
+        self.result = csv_file_path, output_folder
+
+
+def openGlycoDrawExcelDialog():
+    dialog_result = GlycoDrawExcelDialog(app)
+    if dialog_result.result:
+        csv_file_path, output_folder = dialog_result.result
+        plot_glycans_excel(csv_file_path, output_folder)
+
+
+
+class DifferentialExpressionDialog(simpledialog.Dialog):
+    def body(self, master):
+        self.title("Differential Expression Input")
+
+        # CSV file selection
+        tk.Label(master, text="CSV File:").grid(row = 0, sticky = tk.W)
+        self.csv_file_var = tk.StringVar(master)
+        self.csv_entry = tk.Entry(master, textvariable = self.csv_file_var, state = 'readonly')
+        self.csv_entry.grid(row = 0, column = 1)
+        self.csv_browse = tk.Button(master, text = "Browse...", command = self.browse_csv)
+        self.csv_browse.grid(row = 0, column = 2)
+
+        # Output folder selection
+        tk.Label(master, text = "Output Folder:").grid(row = 4, sticky = tk.W)
+        self.output_folder_var = tk.StringVar(master)
+        self.output_folder_entry = tk.Entry(master, textvariable = self.output_folder_var, state = 'readonly')
+        self.output_folder_entry.grid(row = 4, column = 1)
+        self.output_folder_browse = tk.Button(master, text = "Browse...", command = self.browse_output_folder)
+        self.output_folder_browse.grid(row = 4, column = 2)
+
+        # Treatment group indices
+        tk.Label(master, text = "Treatment Group Columns:").grid(row = 1, sticky = tk.W)
+        self.treatment_entry = tk.Entry(master)
+        self.treatment_entry.grid(row = 1, column = 1, columnspan = 2, sticky = tk.W+tk.E)
+
+        # Control group indices
+        tk.Label(master, text = "Control Group Columns:").grid(row = 2, sticky = tk.W)
+        self.control_entry = tk.Entry(master)
+        self.control_entry.grid(row = 2, column = 1, columnspan = 2, sticky = tk.W+tk.E)
+
+        # Motifs option
+        tk.Label(master, text="Motif-based analysis:").grid(row = 3, sticky = tk.W)
+        self.motifs_var = tk.BooleanVar(master)
+        self.motifs_check = tk.Checkbutton(master, variable = self.motifs_var)
+        self.motifs_check.grid(row = 3, column = 1, sticky = tk.W)
+
+        return self.csv_entry  # to put focus on the csv file entry widget
+
+    def apply(self):
+        csv_file_path = self.csv_file_var.get()
+        treatment_indices = self.parse_indices(self.treatment_entry.get())
+        control_indices = self.parse_indices(self.control_entry.get())
+        motifs = self.motifs_var.get()
+        output_folder = self.output_folder_var.get()
+        self.result = csv_file_path, treatment_indices, control_indices, motifs, output_folder
+
+    def parse_indices(self, indices_str):
+        try:
+            # Convert comma-separated string to a list of integers
+            return [int(index.strip()) for index in indices_str.split(',')]
+        except ValueError:
+            # Handle the case where conversion fails
+            messagebox.showerror("Error", "Please enter valid, comma-separated numerical indices.")
+            return []
+
+    def browse_csv(self):
+        file_path = filedialog.askopenfilename(filetypes = [("CSV Files", "*.csv")])
+        if file_path:
+            self.csv_file_var.set(file_path)
+
+    def browse_output_folder(self):
+        folder_path = filedialog.askdirectory()
+        if folder_path:
+            self.output_folder_var.set(folder_path)
+
+
+def openDifferentialExpressionDialog():
+    dialog_result = DifferentialExpressionDialog(app)
+    if dialog_result.result:
+        csv_file_path, treatment_indices, control_indices, motifs, output_folder = dialog_result.result
+        df_out = get_differential_expression(df = csv_file_path,
+                               group1 = treatment_indices,
+                               group2 = control_indices,
+                               motifs = motifs)
+        plot_glycans_excel(df_out, output_folder)
+
+
+app = tk.Tk()
+app.title("glycowork GUI")
+app.geometry("300x150")
+
+btn_function1 = tk.Button(app, text = "Run GlycoDraw", command = openGlycoDrawDialog)
+btn_function1.pack(pady = 5)
+btn_function2 = tk.Button(app, text = "Run GlycoDrawExcel", command = openGlycoDrawExcelDialog)
+btn_function2.pack(pady = 5)
+btn_function3 = tk.Button(app, text="Run DifferentialExpression", command= openDifferentialExpressionDialog)
+btn_function3.pack(pady = 5)
+
+icon_path = resource_path("glycowork.ico")
+app.iconbitmap(icon_path)
+app.mainloop()

build/lib/glycowork/glycan_data/loader.py

@@ -2,14 +2,14 @@
 import os
 import pickle
 import itertools
-import pkg_resources
-
-io = pkg_resources.resource_stream(__name__, "v10_df_species.csv")
-df_species = pd.read_csv(io)
-io = pkg_resources.resource_stream(__name__, "glycan_motifs.csv")
-motif_list = pd.read_csv(io)
-io = pkg_resources.resource_stream(__name__, "glycan_binding.csv")
-glycan_binding = pd.read_csv(io)
+from importlib import resources
+
+with resources.open_text("glycowork.glycan_data", "v10_df_species.csv") as f:
+  df_species = pd.read_csv(f)
+with resources.open_text("glycowork.glycan_data", "glycan_motifs.csv") as f:
+  motif_list = pd.read_csv(f)
+with resources.open_text("glycowork.glycan_data", "glycan_binding.csv") as f:
+  glycan_binding = pd.read_csv(f)
 this_dir, this_filename = os.path.split(__file__)  # Get path of data.pkl
 data_path = os.path.join(this_dir, 'lib_v10.pkl')
 lib = pickle.load(open(data_path, 'rb'))

build/lib/glycowork/motif/tokenization.py

@@ -4,7 +4,7 @@
 import re
 import copy
 import math
-import pkg_resources
+from importlib import resources
 from itertools import product
 from collections import Counter
 from sklearn.cluster import DBSCAN
@@ -17,8 +17,8 @@
          'L':12, 'M':13, 'N':14, 'P':15, 'Q':16, 'R':17, 'S':18, 'T':19,
          'V':20, 'W':21, 'Y':22, 'X':23, 'Z':24, 'z':25}
 
-io = pkg_resources.resource_stream(__name__, "mz_to_composition.csv")
-mapping_file = pd.read_csv(io)
+with resources.open_text("glycowork.motif", "mz_to_composition.csv") as f:
+  mapping_file = pd.read_csv(f)
 mass_dict = dict(zip(mapping_file.composition, mapping_file["underivatized_monoisotopic"]))
 
 

glycowork/glycan_data/loader.py

@@ -2,14 +2,14 @@
 import os
 import pickle
 import itertools
-import pkg_resources
-
-io = pkg_resources.resource_stream(__name__, "v10_df_species.csv")
-df_species = pd.read_csv(io)
-io = pkg_resources.resource_stream(__name__, "glycan_motifs.csv")
-motif_list = pd.read_csv(io)
-io = pkg_resources.resource_stream(__name__, "glycan_binding.csv")
-glycan_binding = pd.read_csv(io)
+from importlib import resources
+
+with resources.open_text("glycowork.glycan_data", "v10_df_species.csv") as f:
+  df_species = pd.read_csv(f)
+with resources.open_text("glycowork.glycan_data", "glycan_motifs.csv") as f:
+  motif_list = pd.read_csv(f)
+with resources.open_text("glycowork.glycan_data", "glycan_binding.csv") as f:
+  glycan_binding = pd.read_csv(f)
 this_dir, this_filename = os.path.split(__file__)  # Get path of data.pkl
 data_path = os.path.join(this_dir, 'lib_v10.pkl')
 lib = pickle.load(open(data_path, 'rb'))

glycowork/glycan_data/stats.py

@@ -573,7 +573,7 @@ def TST_grouped_benjamini_hochberg(identifiers_grouped, p_values_grouped, alpha)
     # Estimate π0 for the group within the Two-Stage method
     pi0_estimate = pi0_tst(group_p_values, alpha)
     if pi0_estimate == 1:
-      adjusted_p_values[identifier] = [1.0] * len(group_p_values)
+      adjusted_p_values[group] = [1.0] * len(group_p_values)
       continue
     n = len(group_p_values)
     sorted_indices = np.argsort(group_p_values)

glycowork/ml/inference.py

@@ -1,17 +1,16 @@
 import pandas as pd
 import numpy as np
-import pkg_resources
+from importlib import resources
 import math
 import torch
 from torch.utils.data import Dataset
 from glycowork.glycan_data.loader import lib, unwrap
 from glycowork.motif.tokenization import prot_to_coded
 from glycowork.ml.processing import dataset_to_dataloader
 
-io = pkg_resources.resource_stream(__name__,
-                                   "glycowork_lectinoracle_background_correction.csv")
 # Background correction values for LectinOracle predictions
-df_corr = pd.read_csv(io)
+with resources.open_text("glycowork.ml", "glycowork_lectinoracle_background_correction.csv") as f:
+  df_corr = pd.read_csv(f)
 
 # Choosing the right computing architecture
 device = "cpu"

glycowork/motif/tokenization.py

@@ -4,7 +4,7 @@
 import re
 import copy
 import math
-import pkg_resources
+from importlib import resources
 from itertools import product
 from collections import Counter
 from sklearn.cluster import DBSCAN
@@ -17,8 +17,8 @@
          'L':12, 'M':13, 'N':14, 'P':15, 'Q':16, 'R':17, 'S':18, 'T':19,
          'V':20, 'W':21, 'Y':22, 'X':23, 'Z':24, 'z':25}
 
-io = pkg_resources.resource_stream(__name__, "mz_to_composition.csv")
-mapping_file = pd.read_csv(io)
+with resources.open_text("glycowork.motif", "mz_to_composition.csv") as f:
+  mapping_file = pd.read_csv(f)
 mass_dict = dict(zip(mapping_file.composition, mapping_file["underivatized_monoisotopic"]))
 
 

glycowork/network/biosynthesis.py

@@ -3,7 +3,7 @@
 import pickle
 import copy
 import os
-import pkg_resources
+from importlib import resources
 import networkx as nx
 import numpy as np
 import pandas as pd
@@ -14,8 +14,8 @@
 from glycowork.motif.tokenization import get_stem_lib
 from glycowork.motif.regex import get_match
 
-io = pkg_resources.resource_stream(__name__, "monolink_to_enzyme.csv")
-df_enzyme = pd.read_csv(io, sep = '\t')
+with resources.open_text("glycowork.network", "monolink_to_enzyme.csv") as f:
+  df_enzyme = pd.read_csv(f, sep = '\t')
 
 this_dir, this_filename = os.path.split(__file__) 
 data_path = os.path.join(this_dir, 'milk_networks_exhaustive.pkl')