MassDash: A web-based dashboard for streamlined DIA-MS visualization, analysis, prototyping, and optimization
Home Page: https://massdash.streamlit.app/
License: BSD 3-Clause "New" or "Revised" License
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File "/media/justincsing/ExtraDrive1/Documents2/Roest_Lab/Github/massdash/massdash/gui.py", line 154, in main
show_search_results_analysis.main()
File "/media/justincsing/ExtraDrive1/Documents2/Roest_Lab/Github/massdash/massdash/server/SearchResultsAnalysisServer.py", line 106, in main
search_results_access_dict = self.load_search_result_entries(self.massseer_gui.file_input_settings.feature_file_entries)
File "/home/justincsing/anaconda3/envs/py39/lib/python3.9/site-packages/streamlit/runtime/caching/cache_utils.py", line 212, in wrapper
return cached_func(*args, **kwargs)
File "/home/justincsing/anaconda3/envs/py39/lib/python3.9/site-packages/streamlit/runtime/caching/cache_utils.py", line 241, in __call__
return self._get_or_create_cached_value(args, kwargs)
File "/home/justincsing/anaconda3/envs/py39/lib/python3.9/site-packages/streamlit/runtime/caching/cache_utils.py", line 267, in _get_or_create_cached_value
return self._handle_cache_miss(cache, value_key, func_args, func_kwargs)
File "/home/justincsing/anaconda3/envs/py39/lib/python3.9/site-packages/streamlit/runtime/caching/cache_utils.py", line 321, in _handle_cache_miss
computed_value = self._info.func(*func_args, **func_kwargs)
File "/media/justincsing/ExtraDrive1/Documents2/Roest_Lab/Github/massdash/massdash/server/SearchResultsAnalysisServer.py", line 51, in load_search_result_entries
data_access = OSWDataAccess(entry_data['search_results_file_path'], mode='gui')
File "/media/justincsing/ExtraDrive1/Documents2/Roest_Lab/Github/massdash/massdash/loaders/access/OSWDataAccess.py", line 76, in __init__
self._initializePeptideHashtable()
File "/media/justincsing/ExtraDrive1/Documents2/Roest_Lab/Github/massdash/massdash/loaders/access/OSWDataAccess.py", line 103, in _initializePeptideHashtable
tmp = pd.read_sql(stmt, self.conn)
File "/home/justincsing/anaconda3/envs/py39/lib/python3.9/site-packages/pandas/io/sql.py", line 564, in read_sql
return pandas_sql.read_query(
File "/home/justincsing/anaconda3/envs/py39/lib/python3.9/site-packages/pandas/io/sql.py", line 2078, in read_query
cursor = self.execute(*args)
File "/home/justincsing/anaconda3/envs/py39/lib/python3.9/site-packages/pandas/io/sql.py", line 2030, in execute
raise ex from exc
pandas.errors.DatabaseError: Execution failed on sql '
SELECT MODIFIED_SEQUENCE, CHARGE, PRECURSOR_ID
FROM PRECURSOR
INNER JOIN PRECURSOR_PEPTIDE_MAPPING ON PRECURSOR_PEPTIDE_MAPPING.PRECURSOR_ID = PRECURSOR.ID
INNER JOIN PEPTIDE ON PEPTIDE.ID = PRECURSOR_PEPTIDE_MAPPING.PEPTIDE_ID': file is not a database
This seems to occur because the downloaded OSW test file is not actually an sqlite osw file
$ head /home/justincsing/Downloads/massdash_example_dataset//test.osw
{"payload":{"allShortcutsEnabled":false,"fileTree":{"test/test_data/example_dia/openswath/osw":{"items":[{"name":"test.osw","path":"test/test_data/example_dia/openswath/osw/test.osw","contentType":"file"}],"totalCount":1},"test/test_data/example_dia/openswath":{"items":[{"name":"lib","path":"test/test_data/example_dia/openswath/lib","contentType":"directory"},{"name":"osw","path":"test/test_data/example_dia/openswath/osw","contentType":"directory"},{"name":"xics","path":"test/test_data/example_dia/openswath/xics","contentType":"directory"}],"totalCount":3},"test/test_data/example_dia":{"items":[{"name":"diann","path":"test/test_data/example_dia/diann","contentType":"directory"},{"name":"dreamdia","path":"test/test_data/example_dia/dreamdia","contentType":"directory"},{"name":"openswath","path":"test/test_data/example_dia/openswath","contentType":"directory"},{"name":"raw","path":"test/test_data/example_dia/raw","contentType":"directory"}],"totalCount":4},"test/test_data":{"items":[{"name":"diann","path":"test/test_data/diann","contentType":"directory"},{"name":"example_dia","pat
$ file /home/justincsing/Downloads/massdash_example_dataset//test.osw
/home/justincsing/Downloads/massdash_example_dataset//test.osw: JSON data
Similarly for the dreamdia test example
$ file /home/justincsing/Downloads/massdash_example_dataset//test_dreamdia_report.tsv
/home/justincsing/Downloads/massdash_example_dataset//test_dreamdia_report.tsv: JSON data
Describe the bug
Unexpected keyword argument (window_size) when selecting conformer for peak picking.
[2024-01-25 13:14:18,645] GenericResultsAccess - INFO - Selected peptide: KVVITAPGGNDVK Selected charge: 2
Pretrained model file: /media/justincsing/ExtraDrive1/Documents2/Roest_Lab/Github/massdash/massdash/ui/../assets/models/conformer/base_cape.onnx
2024-01-25 13:14:18.785 Uncaught app exception
Traceback (most recent call last):
File "/home/justincsing/anaconda3/envs/py39/lib/python3.9/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 535, in _run_script
exec(code, module.__dict__)
File "/media/justincsing/ExtraDrive1/Documents2/Roest_Lab/Github/massdash/massdash/gui.py", line 153, in <module>
main()
File "/home/justincsing/anaconda3/envs/py39/lib/python3.9/site-packages/click/core.py", line 1128, in __call__
return self.main(*args, **kwargs)
File "/home/justincsing/anaconda3/envs/py39/lib/python3.9/site-packages/click/core.py", line 1053, in main
rv = self.invoke(ctx)
File "/home/justincsing/anaconda3/envs/py39/lib/python3.9/site-packages/click/core.py", line 1395, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/home/justincsing/anaconda3/envs/py39/lib/python3.9/site-packages/click/core.py", line 754, in invoke
return __callback(*args, **kwargs)
File "/media/justincsing/ExtraDrive1/Documents2/Roest_Lab/Github/massdash/massdash/gui.py", line 139, in main
show_xic_exp.main()
File "/media/justincsing/ExtraDrive1/Documents2/Roest_Lab/Github/massdash/massdash/server/ExtractedIonChromatogramAnalysisServer.py", line 166, in main
peak_picker = ConformerPeakPicker(self.massdash_gui.file_input_settings.osw_file_path, peak_picking_settings.peak_picker_algo_settings.pretrained_model_file, window_size=peak_picking_settings.peak_picker_algo_settings.conformer_window_size, prediction_threshold=peak_picking_settings.peak_picker_algo_settings.conformer_prediction_threshold, prediction_type=peak_picking_settings.peak_picker_algo_settings.conformer_prediction_type)
TypeError: __init__() got an unexpected keyword argument 'window_size'
To Reproduce
Steps to reproduce the behavior:
Screenshots
Desktop (please complete the following information):
Add an option which performs peak picking on the ms1 level as well. (Turn this on/off in in advanced settings)
2D plotting seems to fail with m/z vs retention time for DIA data. Could be the sparsity when trying to equalize.
Height of peak boundaries are sometimes too high
Peak picking using pyopenms
Describe the bug
When update extraction parameters sometimes plot does not update
Screenshots
Add extraction shaded box to show extraction windows, similar to skyline.
Add an optional extra amount to extraction windows of data to extract for this to make sense/usability. Current extraction, extracts data with the exact windows.
Can add bands to bokeh plot using something like below.
p.xgrid.band_fill_color = "olive"
p.xgrid.band_fill_alpha = 0.1
It would be nice to have an argument to the gui that allows passing a config file with desired workflow and files, so that the application automatically loads require workflow and data instead of opening to the welcome page.
When loading interactive plotter as a python module using
from massseer.plotting import InteractivePlotter
I get the following streamlit warning:
2023-11-15 08:37:21.961 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager
Not sure if there is a way to check if this is being run in a streamlit context or not
Happens during targeted extraction of test file
When setting smoothing to none we get an error.
Although this could be solved by either getting rid of the if condition in chromatogram_plotting_settings these setting do not make sense. We also cannot get rid of these settings all together because these settings are needed for peak picking performed on a chromatogram with None.
Proposed Solution #1: Create seperate sgolay parameters (and advanced pannel) for peak picker MRM. These should by default be the same as sgolay or should be set manually if no sgolay filter is applied
Proposed Solution #2: Perform peak picking directly on raw chromatograms if no sgolay filter.
I'm running into this issue when I call the loadTransitionGroups method from a SqMassLoader object, it only seems to return precursorChrom data and not transitionChrom data. I'm using the test data, so there should be transition data.
I call the sqMassLoader like this:
self.xic_data = SqMassLoader(self.massseer_gui.file_input_settings.sqmass_file_path_list, self.massseer_gui.file_input_settings.osw_file_path)
tr_group_data = self.xic_data.loadTransitionGroups(transition_list_ui.transition_settings.selected_peptide, transition_list_ui.transition_settings.selected_charge)
The Selected peptide: ANS(UniMod:21)SPTTNIDHLK(UniMod:259) and Selected charge: 2
Specifically in the method call for when if gets transitions
transition_chroms = t.getDataForChromatograms(metaInfo['TRANSITION_ID'], metaInfo['PRODUCT_ANNOTATION'])
It seems like metaInfo['TRANSITION_ID'] evaluates to pd,.DataSeries, similar with metaInfo['PRODUCT_ANNOTATION']
metaInfo['TRANSITION_ID']
0 174
1 175
2 176
3 177
4 178
...
384 700416
385 700417
386 700418
387 700419
388 700420
Name: TRANSITION_ID, Length: 389, dtype: int64
metaInfo['PRODUCT_ANNOTATION']
0 y9^1
1 y3^1
2 y7^1
3 y8^1
4 y4^1
...
384 y9^2
385 y9^1
386 y9^1
387 y9^2
388 y9^2
Name: PRODUCT_ANNOTATION, Length: 389, dtype: object
Checking for the length of precursorChrom and transitionChrom in the TransitionGroup object
Length of transition chromatograms: 0
Length of precursor chromatograms: 1
Refactor plotting documentation for easier interaction with python interface/jupyter notebook interface. I am not too sure which strategy would be best.
Some ideas:
Remove the config interface and directly take in parameters on initiation.
plotting methods directly built into structs?
Related to #20
$ pip install -e .
Obtaining file:///mnt/f/Users/JustinS/github/massseer
Installing build dependencies ... done
Checking if build backend supports build_editable ... done
Getting requirements to build editable ... done
Preparing editable metadata (pyproject.toml) ... done
Requirement already satisfied: Click in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from MassSeer==0.1.0a0) (8.1.7) Requirement already satisfied: streamlit in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from MassSeer==0.1.0a0) (1.28.1) Requirement already satisfied: numpy>=1.9.0 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from MassSeer==0.1.0a0) (1.26.1) Requirement already satisfied: pandas>=0.17 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from MassSeer==0.1.0a0) (2.1.2) Requirement already satisfied: cython==0.29.32 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from MassSeer==0.1.0a0) (0.29.32) Requirement already satisfied: scipy in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from MassSeer==0.1.0a0) (1.11.3) Requirement already satisfied: pyopenms in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from MassSeer==0.1.0a0) (3.1.0) Requirement already satisfied: PyMSNumpress==0.2.2 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from MassSeer==0.1.0a0) (0.2.2) Requirement already satisfied: bokeh==2.4.3 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from MassSeer==0.1.0a0) (2.4.3) Requirement already satisfied: matplotlib in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from MassSeer==0.1.0a0) (3.8.1) Requirement already satisfied: Jinja2>=2.9 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from bokeh==2.4.3->MassSeer==0.1.0a0) (3.1.2) Requirement already satisfied: packaging>=16.8 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from bokeh==2.4.3->MassSeer==0.1.0a0) (23.2) Requirement already satisfied: pillow>=7.1.0 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from bokeh==2.4.3->MassSeer==0.1.0a0) (10.1.0) Requirement already satisfied: PyYAML>=3.10 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from bokeh==2.4.3->MassSeer==0.1.0a0) (6.0.1) Requirement already satisfied: tornado>=5.1 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from bokeh==2.4.3->MassSeer==0.1.0a0) (6.3.3) Requirement already satisfied: typing-extensions>=3.10.0 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from bokeh==2.4.3->MassSeer==0.1.0a0) (4.8.0) Requirement already satisfied: python-dateutil>=2.8.2 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from pandas>=0.17->MassSeer==0.1.0a0) (2.8.2) Requirement already satisfied: pytz>=2020.1 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from pandas>=0.17->MassSeer==0.1.0a0) (2023.3.post1) Requirement already satisfied: tzdata>=2022.1 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from pandas>=0.17->MassSeer==0.1.0a0) (2023.3) Requirement already satisfied: contourpy>=1.0.1 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from matplotlib->MassSeer==0.1.0a0) (1.2.0) Requirement already satisfied: cycler>=0.10 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from matplotlib->MassSeer==0.1.0a0) (0.12.1) Requirement already satisfied: fonttools>=4.22.0 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from matplotlib->MassSeer==0.1.0a0) (4.44.0) Requirement already satisfied: kiwisolver>=1.3.1 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from matplotlib->MassSeer==0.1.0a0) (1.4.5) Requirement already satisfied: pyparsing>=2.3.1 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from matplotlib->MassSeer==0.1.0a0) (3.1.1) Requirement already satisfied: importlib-resources>=3.2.0 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from matplotlib->MassSeer==0.1.0a0) (6.1.1) Requirement already satisfied: altair<6,>=4.0 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from streamlit->MassSeer==0.1.0a0) (5.1.2) Requirement already satisfied: blinker<2,>=1.0.0 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from streamlit->MassSeer==0.1.0a0) (1.7.0) Requirement already satisfied: cachetools<6,>=4.0 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from streamlit->MassSeer==0.1.0a0) (5.3.2) Requirement already satisfied: importlib-metadata<7,>=1.4 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from streamlit->MassSeer==0.1.0a0) (6.8.0) Requirement already satisfied: protobuf<5,>=3.20 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from streamlit->MassSeer==0.1.0a0) (4.25.0) Requirement already satisfied: pyarrow>=6.0 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from streamlit->MassSeer==0.1.0a0) (14.0.0) Requirement already satisfied: requests<3,>=2.27 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from streamlit->MassSeer==0.1.0a0) (2.31.0) Requirement already satisfied: rich<14,>=10.14.0 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from streamlit->MassSeer==0.1.0a0) (13.6.0) Requirement already satisfied: tenacity<9,>=8.1.0 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from streamlit->MassSeer==0.1.0a0) (8.2.3) Requirement already satisfied: toml<2,>=0.10.1 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from streamlit->MassSeer==0.1.0a0) (0.10.2) Requirement already satisfied: tzlocal<6,>=1.1 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from streamlit->MassSeer==0.1.0a0) (5.2) Requirement already satisfied: validators<1,>=0.2 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from streamlit->MassSeer==0.1.0a0) (0.22.0) Requirement already satisfied: gitpython!=3.1.19,<4,>=3.0.7 in 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Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit->MassSeer==0.1.0a0) (2023.7.1) Requirement already satisfied: referencing>=0.28.4 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit->MassSeer==0.1.0a0) (0.30.2) Requirement already satisfied: rpds-py>=0.7.1 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit->MassSeer==0.1.0a0) (0.12.0) Requirement already satisfied: mdurl~=0.1 in /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages (from markdown-it-py>=2.2.0->rich<14,>=10.14.0->streamlit->MassSeer==0.1.0a0) (0.1.2)
Building wheels for collected packages: MassSeer
Building editable for MassSeer (pyproject.toml) ... done
Created wheel for MassSeer: filename=MassSeer-0.1.0a0-0.editable-py3-none-any.whl size=5247 sha256=d0e43ba08ed1f714a1a0cd8b5c584e319447b095b0d940eb25a60527c44d773f
Stored in directory: /tmp/pip-ephem-wheel-cache-77l9g1uu/wheels/e8/05/3b/b5068ddd1d07ff8394b3b94438f5416bbf5ab2aef00c613ed0
Successfully built MassSeer
Installing collected packages: MassSeer
Attempting uninstall: MassSeer Found existing installation: MassSeer 0.1.0a0
Uninstalling MassSeer-0.1.0a0:
Successfully uninstalled MassSeer-0.1.0a0 Successfully installed MassSeer-0.1.0a0
(py39) roestlab@DESKTOP-GUU42V4:/mnt/f/Users/JustinS/github/massseer$ MassSeer gui
Traceback (most recent call last): File "/home/roestlab/anaconda3/envs/py39/bin/MassSeer", line 5, in <module>}
from massseer.main import cli ModuleNotFoundError: No module named 'massseer'
It seems that the interactive plot function takes in a list of TransitionGroupFeatures however it does not seem to plot them. Not sure if this is done somewhere else?
A little confusing though for python library usage
Currently playing around more with plotting spectra.
Upon zooming in to the spectra I get an unexpected result. Not sure if this is also present in the streamlit interface.
Possibly have to change to using the vbar command?
Currently the targeted extraction in MzMLDataAccess.py uses pyOpenMS to access the data, but all the extraction / filtering of spectra is done in python. Expose or use extraction methods from pyOpenMS to try speed up extraction, and to be inline with how OpenSwathWorkflow performs extraction.
Solution: If Peak Picking uses OSW-PyProphet Peak boundaries, do not perform peak picking on concensus chromatograms, since this most likely does not make sense.
If someone install this on a fresh environment, they will have troubles with these packages not being installed
Numpy
Scipy
Also, cython for some reason is not installed properly when I used 'pip install -r requirements.txt' If someone calls 'pip install Cython', it will install a version that is not compatible with MSNumpress.
Test data does not get packaged with built and dist package. This causes the Load example data option in the gui to fail since it can't find the test data.
(base) roestlab@DESKTOP-GUU42V4:~$ ls /home/roestlab/anaconda3/envs/py39/lib/python3.9/site-packages/massdash
__init__.py assets gui.py main.py plotting server ui
__pycache__ dataProcessing loaders peakPickers preprocess structs util.py
Add OSW-PyProphet boundaries and scores to chromatograms.
Added in latest commit
Need to add a check for compression level 1, when the data is only zlib compressed. This is usually is not the case if you output a sqMass directly from OpenSwathWorkflow. However, if you output a chrom.mzML and then convert the chrom.mzML to chrom.sqMass, then the compression can be set to 1, zlib only, depending on what flags are set inOpenSwathMzMLFileCacher
Can simply add the following in the _returnDataForChromatogram method
import struct
if compr == 1:
tmp = zlib.decompress(d)
result = struct.unpack("<%sd" % (len(tmp) // 8), tmp)
Note: this assumes the data is 64 bit data. I don't think the sqmass stores what type of data the arrays are stored as, but for 32-bit, we could just do result = struct.unpack("<%sd" % (len(tmp) // 4), tmp)
Mohammed (@alhigaylan) is running into errors when running the app on Mac.
KeyError: 'st.session_state has no key "clicked". Did you forget to initialize it? More info: https://docs.streamlit.io/library/advanced-features/session-state#initialization'
During handling of the above exception, another exception occurred:
File "/opt/anaconda3/envs/mseer/lib/python3.9/multiprocessing/spawn.py", line 125, in _main
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/opt/anaconda3/envs/mseer/lib/python3.9/multiprocessing/spawn.py", line 116, in spawn_main
exitcode = _main(fd, parent_sentinel)
File "/opt/anaconda3/envs/mseer/lib/python3.9/multiprocessing/spawn.py", line 125, in _main
prepare(preparation_data)
File "/opt/anaconda3/envs/mseer/lib/python3.9/multiprocessing/spawn.py", line 236, in prepare
prepare(preparation_data)
File "/opt/anaconda3/envs/mseer/lib/python3.9/multiprocessing/spawn.py", line 236, in prepare
_fixup_main_from_path(data['init_main_from_path'])
File "/opt/anaconda3/envs/mseer/lib/python3.9/multiprocessing/spawn.py", line 287, in _fixup_main_from_path
_fixup_main_from_path(data['init_main_from_path'])
File "/opt/anaconda3/envs/mseer/lib/python3.9/multiprocessing/spawn.py", line 287, in _fixup_main_from_path
main_content = runpy.run_path(main_path,
File "/opt/anaconda3/envs/mseer/lib/python3.9/runpy.py", line 288, in run_path
return _run_module_code(code, init_globals, run_name,
File "/opt/anaconda3/envs/mseer/lib/python3.9/runpy.py", line 97, in _run_module_code
_run_code(code, mod_globals, init_globals,
File "/opt/anaconda3/envs/mseer/lib/python3.9/runpy.py", line 87, in _run_code
main_content = runpy.run_path(main_path,
File "/opt/anaconda3/envs/mseer/lib/python3.9/runpy.py", line 288, in run_path
exec(code, run_globals)
File "/Users/alhigaylan/Desktop/massseer/massseer/gui.py", line 54, in <module>
if st.session_state.clicked['load_toy_dataset']:
File "/opt/anaconda3/envs/mseer/lib/python3.9/site-packages/streamlit/runtime/state/session_state_proxy.py", line 121, in __getattr__
raise AttributeError(_missing_attr_error_message(key))
AttributeError: st.session_state has no attribute "clicked". Did you forget to initialize it? More info: https://docs.streamlit.io/library/advanced-features/session-state#initialization
return _run_module_code(code, init_globals, run_name,
File "/opt/anaconda3/envs/mseer/lib/python3.9/runpy.py", line 97, in _run_module_code
_run_code(code, mod_globals, init_globals,
File "/opt/anaconda3/envs/mseer/lib/python3.9/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/Users/alhigaylan/Desktop/massseer/massseer/gui.py", line 54, in <module>
if st.session_state.clicked['load_toy_dataset']:
File "/opt/anaconda3/envs/mseer/lib/python3.9/site-packages/streamlit/runtime/state/session_state_proxy.py", line 121, in __getattr__
raise AttributeError(_missing_attr_error_message(key))
AttributeError: st.session_state has no attribute "clicked". Did you forget to initialize it? More info: https://docs.streamlit.io/library/advanced-features/session-state#initialization
Traceback (most recent call last):
File "/opt/anaconda3/envs/mseer/lib/python3.9/site-packages/streamlit/runtime/state/session_state.py", line 394, in __getitem__
return self._getitem(widget_id, key)
File "/opt/anaconda3/envs/mseer/lib/python3.9/site-packages/streamlit/runtime/state/session_state.py", line 439, in _getitem
raise KeyError
KeyError
Add logging to code base
Implement a loader for targeted extraction of raw .d data using OpenTims
It seems that toggling on/off the MS2 traces does not change peak picking with the test example is that correct? It seems toggling on/off MS1 traces changes peak picking
Describe the bug
When selecting conformer peak picking, depending on the selected peptide it throws a value error about incorrect dimensions.
ValueError: all the input array dimensions except for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 175 and the array at index 1 has size 1
To Reproduce
Steps to reproduce the behavior:
Expected behavior
Perform peaking picking without error
Screenshots
Desktop (please complete the following information):
See TODO
The following error occurs when using an OSW file and streamlit caching
File "/media/justincsing/ExtraDrive1/Documents2/Roest_Lab/Github/MassSeer/massseer/loaders/access/OSWDataAccess.py", line 118, in _getFeaturesFromPrecursorIdAndRunDf
if check_sqlite_table(self.conn, "SCORE_MS2"):
File "/media/justincsing/ExtraDrive1/Documents2/Roest_Lab/Github/MassSeer/massseer/util.py", line 205, in check_sqlite_table
c = con.cursor()
sqlite3.ProgrammingError: SQLite objects created in a thread can only be used in that same thread. The object was created in thread id 140391240152640 and this is thread id 140391248545344.
Add server.port flag to gui to pass to streamlit to specify port if desired.
streamlit run streamlit_app.py --server.port 8080
By default streamlit uses 8501
Current implementation for averaging, median and percentile_averaging consensus chromatograms can be found here: chromatogram_data_handling.py#L246
Need to refactor and improve logging
Added recipe for bioconda, see bioconda-recipes PR #45189
If there are multiple runs, align the x-axis so the scales are the same.
When conformer peak picking is selected in the raw targeted extraction workflow of the GUI, it doesn't actually do anything, because it's not implemented.
The code to perform peak picking with conformer is here massdash/server/ExtractedIonChromatogramAnalysisServer.py#L158-L171
And needs to be copied to massdash/server/PeakPickingServer.py
NOTE: I don't think PeakPickingServer is even used in RawTargetedExtractionAnalysisServer anymore. It was initially used in the initial implementation, but it was not added in the refactored version. I may have forgot to add it... 🤦
For raw data extraction, there might be times when there is no spectra/chromatogram data found in the raw data for a precursor. The current extraction pipeline returns a dataframe with mz,rt,im, and rt etc, which in this case would be an empty data frame since no data was found.
I want to catch these cases and return a TransitionGroup like object, but want to return an object that indicates the data was not found. I want to catch these cases so that it doesn't just run into an error because theres no data for plotting, but instead prints a message instead of a plot to say that there was no data found etc.
I'm not sure what the best way would be to handle this. Currently I return the TransitionGroup object, and the underlying Chromatogram/Mobilogram objects just get initialized with empty np.arrays.
I could use this and just get the length and say if it's 0, then display some informative message, otherwise print the plot if there is data.
But I would have to iterate through all the objects in TransitioGroup and get all their lengths etc, so I was thinking maybe just creating a dummy class to represent an empty TransitionGroup, and then do a type check to check if the class if TransitionGroup or TransitionGroupEmpty or something like that.
What do you think @jcharkow , or if you know of a better way of handling this?
I think there might be something wrong with the pyPeakPickerMRM implementation, it's not even picking peaks that would be considered peaks?
On the other hand, the MRMTransitionGroupPicker seems to work nicely
But there still is some issue with the area from the TransitionGroupFeature objects. I use the area value to set the hight of the peak boundary bar, but it seems the intensity is greater than the peaks itself
Add a workflow tab to visualize search results, i.e. visualzie target-decoy distribution scores, number of peptides, proteins etc.
Streamlist's dataframe cannot handle large dataframes, which is a known issue because of how they send data. See: streamlit/streamlit#517
ValueError: Message ForwardMsg exceeds maximum protobuf size of 2GB: 2763555001
Will need to add a widget in the sidebar to optionally download the full data, and only maximally show N rows of data when using st.dataframe to visually show data.
A lof of the stuff I refactored needs to have updated documentation. Not sure if @singjc this also applies to you?
I am testing out the plotting module and running into difficulty with getting the plotting functions to work.
Here is my code
from massseer.loaders.SqMassLoader import SqMassLoader
import os
from massseer.plotting.InteractivePlotter import InteractivePlotter
from massseer.plotting.GenericPlotter import PlotConfig
pep = "NKESPT(UniMod:21)KAIVR(UniMod:267)"
charge = 3
pwd = "../tests/test_data/"
loader = SqMassLoader([os.path.join(pwd + "xics/test_chrom_1.sqMass")], os.path.join(pwd + "osw/test_data.osw"))
transitionGroup = list(loader.loadTransitionGroups(pep, charge).values())[0]
pc = PlotConfig()
plotter = InteractivePlotter(pc)
plotter.plot(transitionGroup)
I am running into several errors regarding the title and if I remove the title also getting errors later on, possibly because the methods are not in use anymore.
Look to see if SQL queries could be sped up or if this is a rate limiting factor
Make codebase more "class based" including abstract class based so that it can be more easily extendable. Also this should allow for a friendlier UI for those working directly with the python package.
Several Classes will add include:
Chromatogram - store np arrays of rt and im as well as meta information (e.g. label)
TransitionGroup - an object contaning both the MS1 and the MS2 chromatograms
- possibly some meta information as well
- getMedian() - returns a median chromatogram object
GenericPeakPicker - abstract class containing functions which all peakPickers should implement
- contains pick() function which requires a transition group and returns a list of PeakFeatures
- Current Classes Inhereting from this include:
- pyMRMPeakPicker - Justin's python implementation of MRMPeakPicker
- MRMPeakPicker - Official OpenMS implementation of MRMPeakPicker (from pyopenms)
- Leon's PeakPicker
PeakFeatures - metainformation about a peak feature including rt apex intensity, left width, right width, area intensity etc. These objects created by all peak pickers
ExternalFileLoader - abstract class containing functions to load chromatogram objects
- loadChromatogram() function which takes a peptide sequence as a string and returns a List of TransitionGroup objects (each run)
- loadFeatures() which takes a peptide and loads the features of that peptide into a list of PeakFeatues
- Classes inhereting from this include:
SQMassLoader - inherits from ExternalFileLoader requires osw and list of sqMass files
MzMLLoader - inherits from ExternalFileLoader requires osw/diann results and mzML file
timsLoader - inherits from ExternalFileLoader requires osw/diann results and mzML file
Plotter abstract class for plotting chromatograms
plotTransitionGroup() requires transition group outputs plot
plotPeakFeatures() requires list of peak features and places them on plot
Current Classes Inhereting from this include:
StaticPlot()
InteractivePlot()
streamlit functions hopefully should not change too much.
@singjc Please let me know your thoughts
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