use forms for parameter input

assets/default-params.json

@@ -40,7 +40,7 @@
     "annotate_ms1": false,
     "annotate_ms2": false,
     "use_requant": true,
-    "annotate_gnps_library": true,
+    "annotate_gnps_library": false,
     "annoation_rt_window_sec": 60,
     "annotation_mz_window_ppm": 10,
     "ms1_annotation_file": "",

pages/0_📁_File_Upload.py

@@ -43,6 +43,7 @@
         if cols[1].button("Copy files to workspace", type="primary", disabled=(local_mzML_dir == "")):
             copy_local_mzML_files_from_directory(local_mzML_dir)
 
+mzML_dir = Path(st.session_state.workspace, "mzML-files")
 if any(Path(mzML_dir).iterdir()):
     v_space(2)
     # Display all mzML files currently in workspace

pages/2_🔍_Extracted_Ion_Chromatograms.py

@@ -43,7 +43,6 @@
         "XIC-input-table.tsv",
     )
 
-    st.markdown("**Calculate mass and add to table**")
     c1, c2, c3 = st.columns(3)
     name = c1.text_input(
         "compound name (optional)", "")
@@ -72,11 +71,10 @@
             st.warning("Invalid formula.")
 
 with st.form("eic_form"):
-    st.multiselect("mzML files", [f.stem for f in Path(st.session_state.workspace, "mzML-files").glob("*.mzML")],
+    st.markdown("**Parameters**")
+    st.multiselect("**input mzML files**", [f.stem for f in Path(st.session_state.workspace, "mzML-files").glob("*.mzML")],
                    params["eic_selected_mzML"], key="eic_selected_mzML")
 
-    # Retention time settings
-    st.markdown("**Parameters for chromatogram extraction**")
     c1, c2, c3 = st.columns(3)
     c1.radio(
         "time unit for display", ["seconds", "minutes"], index=["seconds", "minutes"].index(params["eic_time_unit"]), key="eic_time_unit", help="Retention time unit for figures and downloadable tables. Rentention time settings have to be specified in seconds."
@@ -101,8 +99,10 @@
     results_dir = Path(st.session_state.workspace,
                        "extracted-ion-chromatograms")
 
-    _, c2, _ = st.columns(3)
-    submitted = c2.form_submit_button("Extract chromatograms", type="primary")
+    c1, _, c3 = st.columns(3)
+    if c1.form_submit_button("Save Parameters"):
+        save_params(params)
+    submitted = c3.form_submit_button("Extract chromatograms", type="primary")
 
 if submitted:
     mzML_files = [str(Path(st.session_state.workspace,

pages/3_🧪_Untargeted_Metabolomics.py

@@ -13,7 +13,7 @@
     st.markdown(HELP)
 
 with st.form("umetaflow-form"):
-    st.multiselect("mzML files", [f.stem for f in Path(st.session_state.workspace, "mzML-files").glob("*.mzML")],
+    st.multiselect("**sample mzML files**", [f.stem for f in Path(st.session_state.workspace, "mzML-files").glob("*.mzML")],
                    params["umetaflow_selected_mzML"], key="umetaflow_selected_mzML")
     st.markdown("#### 1. Pre-Processing")
     st.markdown("**Feature Detection**")
@@ -56,7 +56,7 @@
     c1, c2 = st.columns(2)
     c1.multiselect(
         "select blank samples",
-        st.session_state["umetaflow_selected_mzML"],
+        [f.stem for f in Path(st.session_state.workspace, "mzML-files").glob("*.mzML")],
         key="blank_files",
         help="The selected samples will be used to calculate avarage feature blank intensities and will not be further processed.",
     )
@@ -224,11 +224,7 @@
         with open(path, "wb") as f:
             f.write(ms1_annotation_file_upload.getbuffer())
         params["ms1_annotation_file"] = str(path)
-    elif params["ms1_annotation_file"]:
-        c2.info(
-            f"Currently selected MS1 library: {Path(params['ms1_annotation_file']).name}")
     else:
-        c2.warning("No MS1 library selected.")
         params["ms1_annotation_file"] = ""
     c1, c2 = st.columns(2)
     c1.number_input(
@@ -259,31 +255,33 @@
         with open(path, "wb") as f:
             f.write(ms2_annotation_file_upload.getbuffer())
         params["ms2_annotation_file"] = str(path)
-    elif params["ms2_annotation_file"]:
-        c2.info(
-            f"Currently selected MS2 library: {Path(params['ms2_annotation_file']).name}")
     else:
-        c2.warning("No MS2 library selected.")
         params["ms2_annotation_file"] = ""
 
     v_space(1)
-    _, c2, _ = st.columns(3)
-    run_button = c2.form_submit_button("Run UmetaFlow", type="primary")
+    c1, _, c3 = st.columns(3)
+    if c1.form_submit_button("Save Parameters"):
+        params = save_params(params)
+    run_button = c3.form_submit_button("Run UmetaFlow", type="primary")
 
 results_dir = Path(st.session_state.workspace, "umetaflow-results")
 if run_button:
     save_params(params)
-    umetaflow_params = load_params()
+    params = load_params()
     # Modify paramters to have float values if necessary
     for key in ("fl_rt_tol", "ad_rt_max_diff", "ma_rt_max", "ffm_noise"):
-        umetaflow_params[key] = float(umetaflow_params[key])
-    mzML_files = [str(Path(st.session_state.workspace,
-                           "mzML-files", f+".mzML")) for f in st.session_state["umetaflow_selected_mzML"]]
-    if mzML_files:
+        params[key] = float(params[key])
+
+    # add blank files to samples which have not been selected as samples
+    mzML_files = params["umetaflow_selected_mzML"]
+    mzML_files += [f for f in params["blank_files"] if f not in params["umetaflow_selected_mzML"]]
+    mzML_files = [str(Path(st.session_state.workspace, "mzML-files", f+".mzML")) for f in mzML_files]
+
+    if len(mzML_files) > len(params["blank_files"]):
         reset_directory(results_dir)
-        run_umetaflow(umetaflow_params, mzML_files, results_dir)
+        run_umetaflow(params, mzML_files, results_dir)
     else:
-        st.warning("No mzML files selected!")
+        st.warning("Check your mzML and blank file selection.")
 
 if results_dir.exists():
     v_space(1)
@@ -432,6 +430,4 @@
                 "Meta Data",
                 md.T.to_csv(sep="\t", index=False),
                 "MetaData.tsv",
-            )
-
-save_params(params)
+            )

src/common.py

@@ -112,25 +112,12 @@ def page_setup(page: str = "") -> dict[str, Any]:
         if "windows" in sys.argv:
             os.chdir("../umetaflow-gui-main")
         # Define the directory where all workspaces will be stored
+        workspaces_dir = Path("..", "workspaces-"+REPOSITORY_NAME)
         if st.session_state.location == "online":
-            workspaces_dir = Path("workspaces-"+REPOSITORY_NAME)
-            # Outside of the repository directory for local and docker
-            # If running in a Docker container, set working directory to the repository directory
-            if "docker" in sys.argv:
-                workspaces_dir = Path("..", "workspaces-"+REPOSITORY_NAME)
-                os.chdir(REPOSITORY_NAME)
+            st.session_state.workspace = Path(workspaces_dir, str(uuid.uuid1()))
         else:
-            workspaces_dir = Path("..", "workspaces-"+REPOSITORY_NAME)
-
-        # If running locally, use the default workspace
-        if "local" in sys.argv:
             st.session_state.workspace = Path(workspaces_dir, "default")
 
-        # If running online, create a new workspace with a random UUID
-        else:
-            st.session_state.workspace = Path(
-                workspaces_dir, str(uuid.uuid1()))
-
     # Make sure the necessary directories exist
     st.session_state.workspace.mkdir(parents=True, exist_ok=True)
     Path(st.session_state.workspace,
@@ -140,11 +127,6 @@ def page_setup(page: str = "") -> dict[str, Any]:
     params = render_sidebar(page)
     return params
 
-
-    # Return the loaded parameters
-    # return params
-
-
 def render_sidebar(page: str = "") -> None:
     """
     Renders the sidebar on the Streamlit app, which includes the workspace switcher,

src/fileupload.py

@@ -7,7 +7,7 @@
 
 
 # Specify mzML file location in workspace
-mzML_dir: Path = Path(st.session_state.workspace, "mzML-files")
+mzML_dir = Path(st.session_state.workspace, "mzML-files")
 
 @st.cache_data
 def save_uploaded_mzML(uploaded_files: list[bytes]) -> None:

src/umetaflow.py

@@ -272,107 +272,106 @@ def additional_data_for_consensus_df(self):
 
 
 def run_umetaflow(params, mzML_files, results_dir):
-    umetaflow = UmetaFlow(params, mzML_files, results_dir)
+    with st.status("Running UmetaFlow", expanded=True) as status:
+        umetaflow = UmetaFlow(params, mzML_files, results_dir)
 
-    with st.spinner("Fetching raw data..."):
+        st.write("Fetching input mzML files...")
         umetaflow.fetch_raw_data()
 
-    with st.spinner("Detecting features..."):
+        st.write("Detecting features...")
         umetaflow.feature_detection()
 
-    if params["remove_blanks"] and len(params["blank_files"]) > 0:
-        with st.spinner("Removing blank features..."):
+        if params["remove_blanks"] and len(params["blank_files"]) > 0:
+            st.write("Removing blank features...")
             umetaflow.remove_blanks()
             if not any(umetaflow.featureXML_dir.iterdir()):
                 st.warning(
                     "No samples left after blank removal! Blank samples will not be further processed."
                 )
                 return
 
-    if params["use_ad"] and not params["use_requant"]:
-        with st.spinner("Determining adducts..."):
+        if params["use_ad"] and not params["use_requant"]:
+            st.write("Determining adducts...")
             umetaflow.adduct_detection()
 
-    # annotate only when necessary
-    if (
-        params["use_sirius_manual"] or params["annotate_ms2"] or params["use_gnps"]
-    ) and not params["use_requant"]:
-        umetaflow.feature_maps_to_df()
-        with st.spinner("Mapping MS2 data to features..."):
+        # annotate only when necessary
+        if (
+            params["use_sirius_manual"] or params["annotate_ms2"] or params["use_gnps"]
+        ) and not params["use_requant"]:
+            umetaflow.feature_maps_to_df()
+            st.write("Mapping MS2 data to features...")
             umetaflow.map_MS2()
 
 
-    if params["use_ma"] and len(list(umetaflow.featureXML_dir.iterdir())) > 1:
-        with st.spinner("Aligning feature maps..."):
+        if params["use_ma"] and len(list(umetaflow.featureXML_dir.iterdir())) > 1:
+            st.write("Aligning feature maps...")
             umetaflow.align_feature_maps()
             umetaflow.feature_maps_to_df()
 
-        with st.spinner("Aligning mzML files..."):
+            st.write("Aligning mzML files...")
             umetaflow.align_peak_maps()
             umetaflow.peak_maps_to_df()
-    else:
-        umetaflow.feature_maps_to_df()
-        umetaflow.peak_maps_to_df()
+        else:
+            umetaflow.feature_maps_to_df()
+            umetaflow.peak_maps_to_df()
 
-    # export only sirius ms files to use in the GUI tool
-    if params["use_sirius_manual"] and not params["use_requant"]:
-        with st.spinner("Exporting files for Sirius..."):
+        # export only sirius ms files to use in the GUI tool
+        if params["use_sirius_manual"] and not params["use_requant"]:
+            st.write("Exporting files for Sirius...")
             umetaflow.sirius()
 
-    with st.spinner("Linking features..."):
+        st.write("Linking features...")
         umetaflow.link_feature_maps()
         umetaflow.consensus_df()
 
-    if params["use_requant"]:
-        # for requant run FFMID and Feature Linking and optionally Adduct Decharging and Mapping MS2 data
-        with st.spinner("Re-quantification..."):
+        if params["use_requant"]:
+            # for requant run FFMID and Feature Linking and optionally Adduct Decharging and Mapping MS2 data
+            st.write("Re-quantification...")
             umetaflow.requantify()
 
-        with st.spinner("Exporting re-quantified feature maps for visualization..."):
+            st.write("Exporting re-quantified feature maps for visualization...")
             umetaflow.feature_maps_to_df(requant=True)
 
-        # annotate only when necessary
-        if params["use_sirius_manual"] or params["annotate_ms2"] or params["use_gnps"]:
-            with st.spinner("Mapping MS2 data to features..."):
+            # annotate only when necessary
+            if params["use_sirius_manual"] or params["annotate_ms2"] or params["use_gnps"]:
+                st.write("Mapping MS2 data to features...")
                 umetaflow.map_MS2()
 
-        if params["use_ad"]:
-            with st.spinner("Determining adducts..."):
+            if params["use_ad"]:
+                st.write("Determining adducts...")
                 umetaflow.adduct_detection()
 
-        if params["use_sirius_manual"]:
-            with st.spinner("Exporting files for Sirius..."):
+            if params["use_sirius_manual"]:
+                st.write("Exporting files for Sirius...")
                 umetaflow.sirius()
 
-        with st.spinner("Linking re-quantified features..."):
+            st.write("Linking re-quantified features...")
             umetaflow.link_feature_maps()
             umetaflow.consensus_df()
 
-    # export metadata
-    umetaflow.export_metadata()
+        # export metadata
+        umetaflow.export_metadata()
 
-    if params["use_gnps"] or params["annotate_ms2"]:
-        with st.spinner("Exporting files for GNPS..."):
+        if params["use_gnps"] or params["annotate_ms2"]:
+            st.write("Exporting files for GNPS...")
             umetaflow.gnps()
 
-    if params["annotate_ms1"]:
-        with st.spinner("Annotating features on MS1 level by m/z and RT"):
+        if params["annotate_ms1"]:
+            st.write("Annotating features on MS1 level by m/z and RT")
             umetaflow.annotate_MS1()
 
-    if (
-        params["annotate_ms2"] and params["ad_ion_mode"] == "positive"
-    ):  # fails with negative mode right now due to wrong charge annotation
-        with st.spinner(
-            "Annotating features on MS2 level by fragmentation patterns..."
-        ):
+        if (
+            params["annotate_ms2"] and params["ad_ion_mode"] == "positive"
+        ):  # fails with negative mode right now due to wrong charge annotation
+            st.write("Annotating features on MS2 level by fragmentation patterns...")
             umetaflow.annotate_MS2()
 
-    umetaflow.additional_data_for_consensus_df()
+        umetaflow.additional_data_for_consensus_df()
 
-    # Export files
-    umetaflow.make_zip_archives()
+        # Export files
+        umetaflow.make_zip_archives()
 
-    st.success("Complete!")
+        status.update(label="UmetaFlow run complete!", state="complete", expanded=False)
 
 
 METABO = {

src/xic.py

@@ -236,7 +236,7 @@ def extract_chromatograms(results_dir, mzML_files, df_input, mz_unit, mz_ppm, mz
         with open(Path(results_dir, "run-params.txt"), "w") as f:
             f.write(f"{baseline}\n{time_unit}")
     # # Re-run to prevent tab jumping back to first tab upon first widget change (streamlit bug)
-    # st.experimental_rerun()
+    st.experimental_rerun()
 
 
 @st.cache_resource