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@@ -26,26 +26,38 @@ QC - Quality Check
 
 #### I - WT processing block
 
-It calculates the background offset for the correction step in the FA. See procedure((#procedure)) below.
+The WT processing block calculates the background offset for the correction step in the FA. See procedure((#procedure)) below.
 
 #### II - main user input
 
-This user input contains general parameters of the FCSpipelineEMBL_KNIME workflow. The explanation of every parameter can be found on the [input parameters](https://git.embl.de/grp-almf/FCSpipelineEMBL_KNIME/-/wikis/input-parameters) page or in a KMIME description menu of the main user inp.
+The main user input contains general parameters of the FCSpipelineEMBL_KNIME workflow. The explanation of every parameter can be found on the [input parameters](https://git.embl.de/grp-almf/FCSpipelineEMBL_KNIME/-/wikis/input-parameters) page or in a KMIME description menu of the main user input.
 
 #### III - plot parameters input
 
-It contains a calibration plot and QC parameters. For parameters' description go to the [input parameters](https://git.embl.de/grp-almf/FCSpipelineEMBL_KNIME/-/wikis/input-parameters) page.
+The plot parameters input contains a calibration plot and QC parameters. For parameter description, go to the [input parameters](https://git.embl.de/grp-almf/FCSpipelineEMBL_KNIME/-/wikis/input-parameters) page.
 
 #### IV - visualization block
 
-
+The block provides visualization of FCSpipelineEMBL_KNIME outputs.
 
 # Procedure 
-1.  Process a WT data with FA to obtain WT.res. A detailed explanation of FA analysis procedure including [correlations calculation](https://git.embl.de/grp-ellenberg/FCSAnalyze/-/wikis/Fa_Load_and_Correlate) and [fitting](https://git.embl.de/grp-ellenberg/FCSAnalyze/-/wikis/Fa_fit_fcs) you can find on git page of FCS-calibrated imaging pipeline developed by Antonio Politi. Perform import, correction, and export steps in FA. Then, fill a WT user input in the KNIME workflow of FCSpipelineEMBL_KNIME and execute Python Source node. Use returned offset value for correction steps in further FA sessions for FP and POI. 
-2.  Perform three separate sessions of FA analysis to obtain FP.res, POI.res, and dye.res as described [here](https://git.embl.de/grp-ellenberg/FCSAnalyze/-/wikis/Fa_fit_fcs). Perform **all** intermediate FA steps (correlations calculation, correction, fitting of correlations with ACF) to obtain mFP.res, POI.res, and dye.res.<br><br>
-  **Important notes:** 
 
--  **Do not forget** to save fluctuation traces with ACF fitting curves (Export all traces button) as .cof, .itr files at the last step of FA analysis
+**Imporatant:** FCSpipelineEMBL_KNIME deals with the outputs of Fluctuation Analyzer. A detailed explanation of FA analysis procedure including [correlations calculation](https://git.embl.de/grp-ellenberg/FCSAnalyze/-/wikis/Fa_Load_and_Correlate) and [fitting](https://git.embl.de/grp-ellenberg/FCSAnalyze/-/wikis/Fa_fit_fcs) can be found on the Wiki page of FCS-calibrated imaging pipeline developed by Antonio Politi.
+
+1.  Process a WT data with FA to obtain WT.res. 
+
+- Perform [import, correction, and export steps in FA](https://git.embl.de/grp-ellenberg/FCSAnalyze/-/wikis/Fa_Load_and_Correlate)
+
+- Fill the WT user input and execute Python Source node. Use returned offset value (right-click -> Table) for correction steps in further FA sessions for FP and POI. 
+
+2.  Perform **all** intermediate steps of FA analysis for POI and FP fluctuation data to obtain mFP.res and POI.res:
+- [correlations calculation and correction](https://git.embl.de/grp-ellenberg/FCSAnalyze/-/wikis/Fa_Load_and_Correlate)
+- [fitting of correlations with ACF](https://git.embl.de/grp-ellenberg/FCSAnalyze/-/wikis/Fa_fit_fcs) and data export 
+<br><be>
+- save (Export all traces button) fluctuation traces with ACF fitting curves for POI and FP.
+
+  **Important notes:** 
+-  **Do not forget** to save (Export all traces button) fluctuation traces with ACF fitting curves for POI and FP.
 -  There are **different fitting models** used for dye and FP&POI.
 -  You can use the default parameters of fit as described [here](https://git.embl.de/grp-ellenberg/FCSAnalyze/-/wikis/Fa_fit_fcs). The parameter N can be calculated as an inverse intersection of correlations plot with the ordinate axis. Then this value of N can be inserted to the table with all parameters. This can help to better convergenсe of parameters used in the fitting model.
 -  If you calculate the effective volume with our pipeline we recommend optimizing the kappa value during the FA fitting step for dye data. For this strategy, run the fitting procedure several times with different kappa near the default meaning. Besides the default kappa given in the instructions of the FA fitting step, one can determine kappa experimentally.