AutoFlowResearch · ghost · Oct 20, 2021 · Oct 20, 2021 · Oct 20, 2021 · Oct 20, 2021
diff --git a/docs/guide/tutorials.rst b/docs/guide/tutorials.rst
@@ -4,8 +4,11 @@ Tutorials & Demos
 This section covers a breadth of walkthroughs using different datasets and analytical techniques.
 
 
-* :doc:`tutorials/Structure_of_Data_Sets`.
-
 * :doc:`tutorials/Targeted_quantitation_with_HPLC_data`.
 
-* :doc:`tutorials/Non-targeted_FIA-MS_analysis_with_Thermo_Orbitrap`.
+* :doc:`tutorials/Non-targeted_FIA-MS_analysis_with_Thermo_Orbitrap`.
+
+* :doc:`tutorials/Targeted_flux_analysis_with_LC-MSMS_Agilent_Lipidomics`.
+
+* :doc:`tutorials/Targeted_flux_analysis_with_GC-MS_SIM_Agilent`.
+
diff --git a/docs/guide/tutorials/Targeted_flux_analysis_with_GC-MS_SIM_Agilent.rst b/docs/guide/tutorials/Targeted_flux_analysis_with_GC-MS_SIM_Agilent.rst
@@ -1,2 +1,97 @@
 Targeted flux analysis with GC-MS SIM Agilent
----------------------------------------------
+---------------------------------------------
+
+This tutorial walks you through the workflow for analyzing targeted flux analysis 
+using SIM GC-MS/MS data starting from input file generation, to processing the data in SmartPeak, 
+to reviewing the data in SmartPeak, to reporting the results for later use.
+
+Objectives
+~~~~~~~~~~
+
+#. Obtaining the SOP for the workflow.
+#. Choosing a data set for demonstrating the workflow.
+#. Creating an optimized SmartPeak input templates for running the workflow.
+
+The Workflows include
+~~~~~~~~~~~~~~~~~~~~~
+
+#. Processing Unknowns
+#. Reviewing the results
+
+Steps
+~~~~~
+
+The tutorial includes the following steps :
+
+#. Setting up the input files
+
+	The data set used can be found here 
+	`GCMS SIM Unknowns <https://github.com/AutoFlowResearch/SmartPeak/tree/develop/src/examples/data/GCMS_SIM_Unknowns>`_.
+
+	The dataset includes a ``parameters.csv`` file containing parameter settings for ``MRMFeatureFinderScoring``, ``MRMFeatureSelector``, 
+	``MRMFeatureValidator``, ``ReferenceDataMethods``, ``MRMFeatureSelector``, ``MRMMapping``, ``FeaturePlotter``, ``SequenceSegmentPlotter``
+	and ``AbsoluteQuantitation``.
+
+
+#. Defining the workflow in SmartPeak
+
+For the targeted flux analysis via SIM GCMS, the following steps are saved 
+into the ``workflow.csv`` file. Alternatively, steps can be replaced, 
+added or deleted direclty from SmartPeakGUI within the "workflow" tap in the right pane. 
+A detailed explanation of each command step
+can be found in :ref:`Workflow Commands`.
+
+	* LOAD_RAW_DATA
+	* MAP_CHROMATOGRAMS
+	* EXTRACT_CHROMATOGRAM_WINDOWS
+	* ZERO_CHROMATOGRAM_BASELINE
+	* PICK_MRM_FEATURES
+	* QUANTIFY_FEATURES
+	* CHECK_FEATURES
+	* SELECT_FEATURES
+	* CALCULATE_MDVS
+	* ISOTOPIC_CORRECTIONS
+	* CALCULATE_MDV_ACCURACIES
+	* STORE_FEATURES
+
+	The workflow pipeline is initialized by loading the raw data followed 
+	by mapping the chromatograms to the loaded set of transitions. Once done,
+	chromatogram windows will be extracted based on the componentFeatureFilter
+	parameters, then for normalizing the lowest chromatogram intensity to zero. The
+	next step in the pipeline is to execute the peak picking routine on the SRM/MRM
+	features followed by applying a calibration model to each transition as defined
+	in the quantitationMethods parameters. Transitions and transition groups are
+	flagged and scored per user pre-defined criteria, then the peak selection/
+	alignment algorithms is executed. Mass distribution vectors can then be 
+	calculated followed by isotopic corrections and comparing the MDVs to the
+	theoretical values. As the final step in the workflow, the features
+	 for the sample group is stored to disk as a ``featureXML`` files.
+
+	To plot the intensities over time for given injections and transitions, view the "chromatogram" from the "view" menu
+	then select the injections and transitions to plot from their respective tabs on the left. The following shows the chromatogram
+	for one injection using Lactate, PEP and Succinate transitions and their intensity differences over time.
+
+	.. image:: ../images/gcms_sim_unknowns_chromatogram.png
+
+	The features can also be plotted as a heatmap, under "view" select "Features (heatmap)" then select the "logSN"
+	feature to display transition groups as a heatmap and compare the values from the same injection as shown below:
+
+	.. image:: ../../images/gcms_sim_unknowns_heatmap.png
+
+	#. Reporting the results
+
+	To export the results, select "Report" from the "Actions" which will show the 
+	"Create Report" window:
+
+	.. image:: ../../images/lcms_targeted_flux_exports.png
+
+	Based in the data you wish to export, select the desired "Sample types" from the left pane
+	and select the "Metadata" from the right pane then click on one of the buttons below to create
+	the report with the selected items in the csv format.
+
+	More details on exporting the results can be found in :ref:`Export report`.
+
+	The resulting ``featureXML`` and ``mzTab`` are saved in the features folder. ``featureXML`` files describe the spectra
+	data for a given injection sample which includes a list of features with a set of ``UserParam`` for each feature such as
+	``PeptideRef``, ``native_id`` and ``scan_polarity``.
+
diff --git a/docs/guide/tutorials/Targeted_flux_analysis_with_LC-MSMS_Agilent_Lipidomics.rst b/docs/guide/tutorials/Targeted_flux_analysis_with_LC-MSMS_Agilent_Lipidomics.rst
@@ -1,2 +1,3 @@
 Targeted flux analysis with LC-MS/MS Agilent Lipidomics
--------------------------------------------------------
+-------------------------------------------------------
+
diff --git a/images/gcms_sim_unknowns_chromatogram.png b/images/gcms_sim_unknowns_chromatogram.png
diff --git a/images/gcms_sim_unknowns_heatmap.png b/images/gcms_sim_unknowns_heatmap.png
diff --git a/images/lcms_targeted_flux_chromatogram.png b/images/lcms_targeted_flux_chromatogram.png
diff --git a/images/lcms_targeted_flux_exports.png b/images/lcms_targeted_flux_exports.png
diff --git a/images/lcms_targeted_flux_spectra.png b/images/lcms_targeted_flux_spectra.png
diff --git a/src/examples/data/GCMS_SIM_Unknowns/parameters.csv b/src/examples/data/GCMS_SIM_Unknowns/parameters.csv
@@ -122,3 +122,7 @@ AbsoluteQuantitation,use_chauvenet,string,FALSE,TRUE,,Whether to only remove out
 AbsoluteQuantitation,optimization_method,string,iterative,iterative,,Calibrator optimization method to find the best set of calibration points for each method.,TRUE,,
 SequenceSegmentPlotter,export_format,string,pdf,pdf,,The export format of the plot,TRUE,,
 SequenceSegmentPlotter,annotate_features,bool,TRUE,,,Annotate peaks with features,TRUE,,
+CalculateMDVs,mass_intensity_type,string,norm_sum,,,,TRUE,,
+CalculateMDVs,feature_name,string,peak_apex_int,,,,TRUE,,
+IsotopicCorrections,correction_matrix_agent,string,TBDMS,,,,TRUE,,
+CalculateMDVAccuracies,feature_name,string,peak_apex_int,,,,TRUE,,