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New release #47

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merged 4 commits into from
Sep 19, 2024
Merged

New release #47

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33d5ccb
adjust fdr estimation
t0mdavid-m Sep 19, 2024
e38c7a9
remove unused workflow
t0mdavid-m Sep 19, 2024
365ca3e
refactor simple workflow functions
t0mdavid-m Sep 19, 2024
9902b58
update component
t0mdavid-m Sep 19, 2024
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2 changes: 1 addition & 1 deletion js-component/dist/assets/index-b13b8b6b.css → js-component/dist/assets/index-092a80e1.css
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6 changes: 3 additions & 3 deletions js-component/dist/assets/index-a1fef4ec.js → js-component/dist/assets/index-6992900e.js
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4 changes: 2 additions & 2 deletions js-component/dist/index.html
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Original file line number Diff line number Diff line change
Expand Up @@ -5,8 +5,8 @@
<link rel="icon" href="./favicon.ico" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>openms-streamlit-vue-component</title>
<script type="module" crossorigin src="./assets/index-a1fef4ec.js"></script>
<link rel="stylesheet" href="./assets/index-b13b8b6b.css">
<script type="module" crossorigin src="./assets/index-6992900e.js"></script>
<link rel="stylesheet" href="./assets/index-092a80e1.css">
</head>
<body>
<div id="app"></div>
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138 changes: 30 additions & 108 deletions src/Workflow.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
import streamlit as st
import multiprocessing
import json
import sys
import time
from .workflow.WorkflowManager import WorkflowManager
Expand All @@ -11,85 +12,6 @@
from shutil import copyfile, rmtree
from pathlib import Path

class Workflow(WorkflowManager):
# Setup pages for upload, parameter, execution and results.
# For layout use any streamlit components such as tabs (as shown in example), columns, or even expanders.
def __init__(self) -> None:
# Initialize the parent class with the workflow name.
super().__init__("TOPP Workflow", st.session_state["workspace"])

def upload(self)-> None:
t = st.tabs(["MS data", "Example with fallback data"])
with t[0]:
# Use the upload method from StreamlitUI to handle mzML file uploads.
self.ui.upload_widget(key="mzML-files", name="MS data", file_type="mzML")
with t[1]:
# Example with fallback data (not used in workflow)
self.ui.upload_widget(key="image", file_type="png", fallback="assets/OpenMS.png")

def configure(self) -> None:
# Allow users to select mzML files for the analysis.
self.ui.select_input_file("mzML-files", multiple=True)

# Create tabs for different analysis steps.
t = st.tabs(
["**Feature Detection**", "**Adduct Detection**", "**SIRIUS Export**", "**Python Custom Tool**"]
)
with t[0]:
# Parameters for FeatureFinderMetabo TOPP tool.
self.ui.input_TOPP("FeatureFinderMetabo")
with t[1]:
# A single checkbox widget for workflow logic.
self.ui.input_widget("run-adduct-detection", False, "Adduct Detection")
# Paramters for MetaboliteAdductDecharger TOPP tool.
self.ui.input_TOPP("MetaboliteAdductDecharger")
with t[2]:
# Paramters for SiriusExport TOPP tool
self.ui.input_TOPP("SiriusExport")
with t[3]:
# Generate input widgets for a custom Python tool, located at src/python-tools.
# Parameters are specified within the file in the DEFAULTS dictionary.
self.ui.input_python("example")

def execution(self) -> None:
# Get mzML input files from self.params.
# Can be done without file manager, however, it ensures everything is correct.
in_mzML = self.file_manager.get_files(self.params["mzML-files"])

# Log any messages.
self.logger.log(f"Number of input mzML files: {len(in_mzML)}")

# Prepare output files for feature detection.
out_ffm = self.file_manager.get_files(in_mzML, "featureXML", "feature-detection")

# Run FeatureFinderMetabo tool with input and output files.
self.executor.run_topp(
"FeatureFinderMetabo", input_output={"in": in_mzML, "out": out_ffm}
)

# Check if adduct detection should be run.
if self.params["run-adduct-detection"]:

# Run MetaboliteAdductDecharger for adduct detection, with disabled logs.
# Without a new file list for output, the input files will be overwritten in this case.
self.executor.run_topp(
"MetaboliteAdductDecharger", {"in": out_ffm, "out_fm": out_ffm}, write_log=False
)

# Example for a custom Python tool, which is located in src/python-tools.
self.executor.run_python("example", {"in": in_mzML})

# Prepare output file for SiriusExport.
out_se = self.file_manager.get_files("sirius.ms", set_results_dir="sirius-export")
self.executor.run_topp("SiriusExport", {"in": self.file_manager.get_files(in_mzML, collect=True),
"in_featureinfo": self.file_manager.get_files(out_ffm, collect=True),
"out": out_se})

def results(self) -> None:
st.warning("Not implemented yet.")




class TagWorkflow(WorkflowManager):

Expand All @@ -103,36 +25,36 @@ def upload(self)-> None:
t = st.tabs(["MS data", "Database"])
with t[0]:
example_data = ['example-data/flashtagger/example_spectrum_%d.mzML' % n for n in [1, 2]]
# Use the upload method from StreamlitUI to handle mzML file uploads.
self.ui.upload_widget(key="mzML-files", name="MS data", file_type="mzML", fallback=example_data)
with t[1]:
# Example with fallback data (not used in workflow)
self.ui.upload_widget(key="fasta-file", name="Database", file_type="fasta", enable_directory=False,
fallback='example-data/flashtagger/example_database.fasta')


def configure(self) -> None:
# Allow users to select mzML files for the analysis.
# Input File Selection
self.ui.select_input_file("mzML-files", multiple=True)
self.ui.select_input_file("fasta-file", multiple=False)

# Number of threads cannot be selected in online mode
if 'local' in sys.argv:
self.ui.input_widget(
'threads', name='threads', default=multiprocessing.cpu_count(),
help='The number of threads that should be used to run the tools.'
)

# Decoy database size toggle
self.ui.input_widget(
'few_proteins', name='Do you expect <100 Proteins?', widget_type='checkbox', default=True,
help='If set, the decoy database will be 10 times larger than the target database for better FDR estimation resolution. This increases the runtime significantly.'
)

# Create tabs for different analysis steps.
# Create tabs for different analysis steps
t = st.tabs(
["**FLASHDeconv**", "**FLASHTnT**"]
)
with t[0]:
# Parameters for FeatureFinderMetabo TOPP tool.
# FLASHDeconv Configuration
self.ui.input_TOPP(
'FLASHDeconv',
exclude_parameters = [
Expand All @@ -145,17 +67,9 @@ def configure(self) -> None:
display_subsections=True
)
with t[1]:
# Parameters for FeatureFinderMetabo TOPP tool.
self.ui.input_TOPP(
'FLASHTnT',
#exclude_parameters = [
# 'min_mz', 'max_mz', 'min_rt', 'max_rt', 'max_ms_level',
# 'use_RNA_averagine', 'tol', 'min_mass', 'max_mass',
# 'min_charge', 'max_charge', 'precursor_charge',
# 'precursor_mz', 'min_cos', 'min_snr'
#],
display_subsections=True
)
# FLASHTnT Configuration
self.ui.input_TOPP('FLASHTnT', display_subsections=True)


def pp(self) -> None:

Expand Down Expand Up @@ -262,7 +176,9 @@ def execution(self) -> None:
makedirs(folder_path)

tagger_params = self.executor.parameter_manager.get_parameters_from_json()['FLASHTnT']
if ('Tagger:fdr' in tagger_params) and (tagger_params['Tagger:fdr'] < 1):

if ((tagger_params.get('tnt:prsm_fdr', 1) < 1) or (tagger_params.get('tnt:pro_fdr', 1) < 1)):

if self.executor.parameter_manager.get_parameters_from_json()['few_proteins']:
ratio = 10
else:
Expand Down Expand Up @@ -309,17 +225,24 @@ def execution(self) -> None:
}
)

uploaded_files.append(out_db)
uploaded_files.append(out_anno)
uploaded_files.append(out_deconv)
uploaded_files.append(out_tag)
uploaded_files.append(out_protein)
# uploaded_files.append(out_db)
# uploaded_files.append(out_anno)
# uploaded_files.append(out_deconv)
# uploaded_files.append(out_tag)
# uploaded_files.append(out_protein)

copyfile(out_db, join(folder_path, 'database.fasta'))
copyfile(out_anno, join(folder_path, 'annotated.mzML'))
copyfile(out_deconv, join(folder_path, 'out.mzML'))
copyfile(out_tag, join(folder_path, 'tags.tsv'))
copyfile(out_protein, join(folder_path, 'proteins.tsv'))

for tool in ['FLASHDeconv', 'FLASHTnT']:
with open(join(folder_path, f'settings_{tool}.json')):
json.dump(
self.executor.parameter_manager.get_parameters_from_json()[tool],
indent='\t'
)


# make directory to store deconv and anno mzML files & initialize data storage
Expand Down Expand Up @@ -370,26 +293,25 @@ def __init__(self) -> None:


def upload(self)-> None:
# Use the upload method from StreamlitUI to handle mzML file uploads.
self.ui.upload_widget(key="mzML-files", name="MS data", file_type="mzML",
fallback=['example-data/flashdeconv/example_fd.mzML'])


def configure(self) -> None:
# Allow users to select mzML files for the analysis.
# Input File Selection
self.ui.select_input_file("mzML-files", multiple=True)

# Number of threads cannot be selected in online mode
if 'local' in sys.argv:
self.ui.input_widget(
'threads', name='threads', default=multiprocessing.cpu_count(),
help='The number of threads that should be used to run the tools.'
)


# FLASHDeconv Configuration
self.ui.input_TOPP(
'FLASHDeconv',
exclude_parameters = [
'ida_log'
],
display_subsections=True
'FLASHDeconv', exclude_parameters = ['ida_log'], display_subsections=True
)


Expand Down
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