Merge pull request #42 from MannLabs/development

Release 1.3.1

alphadia/__init__.py

@@ -2,7 +2,7 @@
 
 
 __project__ = "alphadia"
-__version__ = "1.3.0"
+__version__ = "1.3.1"
 __license__ = "Apache"
 __description__ = "An open-source Python package of the AlphaPept ecosystem"
 __author__ = "Mann Labs"

alphadia/extraction/data.py

@@ -714,7 +714,51 @@ def get_dense(
             absolute_masses = absolute_masses
         )
 
-@nb.njit()
+import numba as nb
+@alphatims.utils.pjit()
+def transpose_chunk(
+        chunk_idx,
+        chunks,
+        push_indices,
+        push_indptr,
+        tof_indices,
+        tof_indptr,
+        values,
+        new_values,
+        tof_indcount
+    ):
+
+    tof_index_chunk_start = chunks[chunk_idx]
+    tof_index_chunk_stop = chunks[chunk_idx+1]
+
+    for push_idx in range(len(push_indptr)-1):
+        start_push_indptr = push_indptr[push_idx]
+        stop_push_indptr = push_indptr[push_idx + 1]
+
+        for idx in range(start_push_indptr, stop_push_indptr):
+            # new row
+            tof_index = tof_indices[idx]
+            if tof_index_chunk_start <= tof_index and tof_index < tof_index_chunk_stop:
+                push_indices[tof_indptr[tof_index] + tof_indcount[tof_index]] = push_idx
+                new_values[tof_indptr[tof_index] + tof_indcount[tof_index]] = values[idx]
+                tof_indcount[tof_index] += 1
+
+@nb.njit
+def build_chunks(number_of_elements, num_chunks):
+    # Calculate the number of chunks needed
+    chunk_size = (number_of_elements + num_chunks - 1) // num_chunks
+
+    chunks = [0]
+    start = 0
+
+    for _ in range(num_chunks):
+        stop = min(start + chunk_size, number_of_elements)
+        chunks.append(stop)
+        start = stop
+
+    return np.array(chunks)
+
+@nb.njit
 def transpose(
         tof_indices,
         push_indptr,
@@ -741,6 +785,9 @@ def transpose(
     values : np.ndarray
         values (n_values)
 
+    threads : int
+        number of threads to use
+
     Returns
     -------
 
@@ -774,18 +821,23 @@ def transpose(
     # get new values
     push_indices = np.zeros((len(tof_indices)), dtype=np.uint32)
     new_values = np.zeros_like(values)
-
-    for push_idx in range(len(push_indptr)-1):
-        start_push_indptr = push_indptr[push_idx]
-        stop_push_indptr = push_indptr[push_idx + 1]
-
-        for idx in range(start_push_indptr, stop_push_indptr):
-
-            # new row
-            tof_index = tof_indices[idx]
-
-            push_indices[tof_indptr[tof_index] + tof_indcount[tof_index]] = push_idx
-            new_values[tof_indptr[tof_index] + tof_indcount[tof_index]] = values[idx]
-            tof_indcount[tof_index] += 1
+
+    chunks = build_chunks(max_tof_index+1, 20)
+
+    with nb.objmode:
+        alphatims.utils.set_threads(20)
+
+        transpose_chunk(
+            range(len(chunks)-1),
+            chunks,
+            push_indices,
+            push_indptr,
+            tof_indices,
+            tof_indptr,
+            values,
+            new_values,
+            tof_indcount,
+
+        )
 
     return push_indices, tof_indptr, new_values

alphadia/extraction/fdr.py

@@ -171,7 +171,8 @@ def fdr_to_q_values(
 def get_q_values(
         _df : pd.DataFrame,
         score_column : str = 'proba',
-        decoy_column : str = '_decoy'
+        decoy_column : str = '_decoy',
+        qval_column : str = 'qval'
     ):
     """Calculates q-values for a dataframe containing PSMs.
     
@@ -189,6 +190,9 @@ def get_q_values(
         The name of the column containing the decoy information. 
         Decoys are expected to be 1 and targets 0.
 
+    qval_column : str, default='qval'
+        The name of the column to store the q-values in.
+
     Returns
     -------
 
@@ -201,7 +205,7 @@ def get_q_values(
     decoy_cumsum = np.cumsum(_df[decoy_column].values)
     target_cumsum = np.cumsum(target_values)
     fdr_values = decoy_cumsum/target_cumsum
-    _df['qval'] = fdr_to_q_values(fdr_values)
+    _df[qval_column] = fdr_to_q_values(fdr_values)
     return _df
 
 def plot_fdr(

alphadia/extraction/hybridselection.py

@@ -1308,8 +1308,9 @@ def append_precursor_information(
 
         df['flat_frag_start_idx'] = self.precursors_flat['flat_frag_start_idx'].values[precursor_flat_lookup]
         df['flat_frag_stop_idx'] = self.precursors_flat['flat_frag_stop_idx'].values[precursor_flat_lookup]
-
         df['charge'] = self.precursors_flat['charge'].values[precursor_flat_lookup]
+        df['proteins'] = self.precursors_flat['proteins'].values[precursor_flat_lookup]
+        df['genes'] = self.precursors_flat['genes'].values[precursor_flat_lookup]
 
         available_isotopes = utils.get_isotope_columns(self.precursors_flat.columns)
         available_isotope_columns = [f'i_{i}' for i in available_isotopes]

alphadia/extraction/planning.py

@@ -339,6 +339,10 @@ def build_output(self):
 
         for raw_name, dia_path, speclib in self.get_run_data():
             run_path = os.path.join(temp_path, raw_name)
+            psm_path = os.path.join(run_path, 'psm.tsv')
+            if not os.path.exists(psm_path):
+                logger.warning(f'no psm file found for {raw_name}')
+                continue
             run_df = pd.read_csv(os.path.join(run_path, 'psm.tsv'), sep='\t')
 
             psm_df.append(run_df)

alphadia/extraction/plexscoring.py

@@ -1440,7 +1440,9 @@ def collect_candidates(
             'decoy',
             'channel',
             'flat_frag_start_idx',
-            'flat_frag_stop_idx'
+            'flat_frag_stop_idx',
+            'proteins',
+            'genes'
         ] + utils.get_isotope_column_names(self.precursors_flat_df.columns)
         df = utils.merge_missing_columns(
             df,

alphadia/extraction/workflow/manager.py

@@ -556,7 +556,7 @@ def get_classifier(self, available_columns):
             classifier = self.classifier_store[classifier_hash]
         else:
             classifier = sklearn.base.clone(self.classifier_base)
-
+        return classifier
         if isinstance(classifier, sklearn.pipeline.Pipeline):
             for step in classifier.steps:
                 if hasattr(step[1], 'warm_start'):

alphadia/extraction/workflow/peptidecentric.py

@@ -359,8 +359,11 @@ def calibration(self):
                     self.recalibration(precursor_df, fragments_df)
                     break
                 else:
-                    pass
-
+                    # check if last step has been reached
+                    if current_step == len(self.batch_plan) - 1:
+                        logger.info('Searched all data without finding recalibration target')
+                        raise RuntimeError('Searched all data without finding recalibration target')
+
             self.end_of_epoch()
 
         if 'final_full_calibration' in self.config['calibration']:
@@ -454,9 +457,6 @@ def check_recalibration(self, precursor_df):
 
         if self.com.accumulated_precursors_001FDR > self.com.recalibration_target:
             perform_recalibration = True
-
-        if self.com.current_step == len(self.batch_plan) -1:
-            perform_recalibration = True
 
         return perform_recalibration
 
@@ -640,7 +640,7 @@ def requantify(
         psm_df = self.fdr_manager.fit_predict(
             multiplexed_features,
             decoy_strategy='channel',
-            competetive = self.config['fdr']['competetive_scoring'],
+            competetive = self.config['multiplexing']['competetive_scoring'],
             decoy_channel=decoy_channel,
         )
 

gui/package.json

@@ -1,7 +1,7 @@
 {
   "name": "alphadia",
   "productName": "alphadia-gui",
-  "version": "1.3.0",
+  "version": "1.3.1",
   "description": "Graphical user interface for DIA data analysis",
   "main": "dist/electron.js",
   "homepage": "./",

gui/src/main/electron.js

@@ -1,4 +1,4 @@
-const { app, BrowserWindow, ipcMain, dialog, shell, nativeTheme } = require('electron')
+const { app, BrowserWindow, Menu, ipcMain, dialog, shell, nativeTheme } = require('electron')
 const osu = require('node-os-utils')
 const path = require("path");
 const writeYamlFile = require('write-yaml-file')
@@ -7,14 +7,17 @@ const os = require('os')
 
 const { handleGetSingleFolder,handleGetMultipleFolders, handleGetSingleFile, handleGetMultipleFiles} = require('./modules/dialogHandler')
 const { discoverWorkflows, workflowToConfig } = require('./modules/workflows')
-const { getEnvironmentStatus, lineBreakTransform, CondaEnvironment} = require('./modules/cmd');
+const { CondaEnvironment} = require('./modules/cmd');
+const { buildMenu } = require('./modules/menu')
+const { Profile } = require('./modules/profile')
 
 // Handle creating/removing shortcuts on Windows when installing/uninstalling.
 if (require('electron-squirrel-startup')) app.quit();
 
 let mainWindow;
 let workflows;
 let environment;
+let profile;
 
 function createWindow() {
   // Create the browser window.
@@ -32,14 +35,18 @@ function createWindow() {
     },
   });
     mainWindow.setTitle("alphaDIA");
-    mainWindow.removeMenu()
     mainWindow.loadFile(path.join(__dirname, "../dist/index.html"));
 
+    profile = new Profile()
+
+    Menu.setApplicationMenu(buildMenu(mainWindow, profile));
+
     // Open the DevTools if NODE_ENV=dev
     if (process.env.NODE_ENV === "dev"){
         mainWindow.webContents.openDevTools({ mode: "detach" });
     }
-    environment = new CondaEnvironment("alpha")
+
+    environment = new CondaEnvironment(profile)
     workflows = discoverWorkflows(mainWindow)
 }
 
@@ -82,7 +89,7 @@ function handleStartWorkflow(workflow) {
     // save config.yaml in workflow folder
     writeYamlFile.sync(configPath, config, {lineWidth: -1})
 
-    return environment.spawn(`conda run -n ${environment.envName} --no-capture-output alphadia extract --config ${configPath}`)
+    return environment.spawn(`conda run -n ${profile.config.conda.envName} --no-capture-output alphadia extract --config ${configPath}`)
 }
 
 // This method will be called when Electron has finished
@@ -122,15 +129,6 @@ app.whenReady().then(() => {
     powerMonitor.on("suspend", () => {
         powerSaveBlocker.start("prevent-app-suspension");
     });
-
-    mainWindow.webContents.on('render-process-gone', function (event, detailed) {
-        console.log("!crashed, reason: " + detailed.reason + ", exitCode = " + detailed.exitCode)
-        if (detailed.reason == "crashed"){
-            // relaunch app
-            app.relaunch({ args: process.argv.slice(1).concat(['--relaunch']) })
-            app.exit(0)
-        }
-    })
 });
 
 app.on('window-all-closed', () => {