diff --git a/2_GeneralScripts/FilterStructArray_by_PH.m b/2_GeneralScripts/FilterStructArray_by_PH.m
new file mode 100644
index 0000000..6e6c57d
--- /dev/null
+++ b/2_GeneralScripts/FilterStructArray_by_PH.m
@@ -0,0 +1,97 @@
+%
+%
+%%%%%%%%%%%%%%%%   FilterStructArray created by Philipp  %%%%%%%%%%%%%%%%%%%%%%%%
+%
+%
+% What this script does: It loads a struct saved in .mat file and
+% filters/removes each row for given criteria. Can save to a new .mat file.
+% Example usage: filter AccMM2Genes.mat for A2_List2Genes
+%
+% Also, one could use it for existing workspace variables by replacing all
+% occurencies of loadedStruct.(nameOfStruct) with the variable name, BUT
+% it should be easier just to save it with right-click in workspace view
+% and use as intended.
+% 
+%    input:
+%%%%     -- .mat file with struct to load
+%%%%     -- parameters
+%%%%     -- criteria for rows to filter out in line 66
+%    output:
+%%%%     -- filtered .mat file with rows hitting criteria missing
+
+%% settings %%
+
+% the .mat file with a struct to load
+pathOfMatFile = "C:\Users\[username]\...\file.mat";
+% whether to save filtered .mat file
+shallFileBeSaved = true;
+% the path where to save the filtered .mat file
+pathToSave = "C:\Users\[username]\...\file_filtered.mat";
+% name of the struct that was saved/should be filtered
+nameOfStruct = "xxx"; % e.g. "MultiHitStat"
+% field name / column to apply critera on
+fieldToCheck = "xxx"; %e.g. "FracMean"
+
+%%%% CHANGE CRITERIA BELOW %%%%
+%%%% you just have to edit the criteria below this line %%%%
+
+
+%% load struct from .mat file into variable loadedStruct
+try
+    loadedStruct = load(pathOfMatFile);
+% on errors
+catch ME
+    % show error
+    disp(ME);
+    % handle wrong file format
+    if ME.identifier == "MATLAB:load:numColumnsNotSame"
+        error("Error loading file. Is it a valid .mat file?");
+    % handle file missing
+    elseif ME.identifier == "MATLAB:load:couldNotReadFile"
+        error('Error loading file. The path correct? It should end with ".mat"');
+    end
+end
+disp("The file " + pathOfMatFile + " was loaded.")
+
+%% initialize list of rows to delete
+rowsToDelete = [];
+
+%% go through the whole struct (2nd dimenstion of struct size)
+% and check criteria
+for i=1:size(loadedStruct.(nameOfStruct),2);
+    % if this criteria is hit, then mark for deletion
+    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+    %%%%%%%% change this criterion as you need it %%%%%%%%%%%%%%%
+    %%%%%%%%      here it is: "equals zero"      %%%%%%%%%%%%%%%%
+    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+    if loadedStruct.(nameOfStruct)(i).(fieldToCheck) == 0
+        % mark for deletion
+        rowsToDelete = [rowsToDelete, uint32(i)];
+    end
+end
+
+%% delete (fill with empty) the marked rows of the struct
+loadedStruct.(nameOfStruct)(rowsToDelete) = [];
+%% print how many rows were deleted
+disp("From " + string(structLengths(2)) + " rows, " ...
+    + string(size(rowsToDelete,2)) + " were deleted.");
+
+%% save new .mat if enabled
+if shallFileBeSaved
+    try
+        save(pathToSave, "-struct", "loadedStruct");
+    % on errors
+    catch ME
+        disp(ME);
+        % handle parent directory missing
+        if ME.identifier == "MATLAB:save:noParentDir"
+            error("Error, the given directory to save the file " + ...
+                "seems to be missing or incorrect.");
+        end
+    end
+    % display if successful
+    disp("Filtered .mat was saved to " + pathToSave);
+else
+    disp("The filtered struct was not saved. You may do it on your " + ...
+        "own using the workspace.");
+end
\ No newline at end of file
diff --git a/README.md b/README.md
index 09f85dc..de52ef2 100644
--- a/README.md
+++ b/README.md
@@ -6,6 +6,12 @@ The pipeline is visualized in the following scheme:
   
 <img src="https://github.com/Easybel/DetectionGV/blob/main/Pipeline_WGS.png" width="900">
 
+A more detailed diagram can be found on LucidChart <https://lucid.app/documents/view/fa9f52da-edf4-4fb2-9b6c-d01996f4768e> or under [/documentation](/documentation)
+
+Preview:
+
+<img src="https://github.com/Easybel/DetectionGV/blob/main/documentation/DetectionGV_preview.png" width="900">
+
 # Overview of folders and scripts
 - **[0_WGSPipeline](https://github.com/Easybel/DetectionGV/tree/main/0_WGSPipeline)**  
   - This contains all bioinformatic scripts needed to analyse whole genome, raw sequencing reads of bacterial transformation hybrids.
diff --git a/documentation/DetectionGV.csv b/documentation/DetectionGV.csv
new file mode 100644
index 0000000..59027cb
--- /dev/null
+++ b/documentation/DetectionGV.csv
@@ -0,0 +1,209 @@
+Id,Name,Shape Library,Page ID,Contained By,Group,Line Source,Line Destination,Source Arrow,Destination Arrow,Status,Text Area 1,Text Area 2,Text Area 3,Text Area 4,Text Area 5,Text Area 6,Text Area 7,Comments
+1,Document,,,,,,,,,Draft,DetectionGV,,,,,,,
+2,Page,,,,,,,,,,Page 1,,,,,,,
+3,Cloud,Geometric Shapes,2,,,,,,,,3_CombiScriptInsertions.sh,,,,,,,
+4,Cloud,Geometric Shapes,2,,,,,,,,2_CombiScriptSamtools.sh,,,,,,,
+5,Cloud,Geometric Shapes,2,,,,,,,,1_QCScript.sh,,,,,,,
+6,Cloud,Geometric Shapes,2,,,,,,,,0_DicIndex.sh,,,,,,,
+7,DividerBlock,,2,,,,,,,,,,,,,,,
+8,Decision,Flowchart Shapes/Containers,2,,,,,,,,.fasta    (recipient WT),,,,,,,
+9,Text,Standard,2,,,,,,,,Trimmomatic trimmomatic PE,,,,,,,
+10,Decision,Flowchart Shapes/Containers,2,,,,,,,,raw reads .fastq(.gz) of hybrids,,,,,,,
+11,Text,Standard,2,,,,,,,,Align reads to reference genome (recipient wild type) bwa mem -B 1 -O 1,,,,,,,
+12,Text,Standard,2,,,,,,,,FastQC fastqc,,,,,,,
+13,Decision,Flowchart Shapes/Containers,2,,,,,,,,quality reports .zip/.html,,,,,,,
+14,Text,Standard,2,,,,,,,,pile up bcftools mpileup,,,,,,,
+15,Decision,Flowchart Shapes/Containers,2,,,,,,,,_2Ref_bcf.vcf,,,,,,,
+16,Text,Standard,2,,,,,,,,calculate coverage with BedTools genomeCoverageBed,,,,,,,
+17,Decision,Flowchart Shapes/Containers,2,,,,,,,,coverage _2Ref_coverage.txt,,,,,,,
+18,Text,Standard,2,,,,,,,,"""Hard"" align reads to donor genome (recipient wild type) bwa mem",,,,,,,
+19,Decision,Flowchart Shapes/Containers,2,,,,,,,,_2Donor.sam,,,,,,,
+20,Text,Standard,2,,,,,,,,sort samtools sort,,,,,,,
+21,Decision,Flowchart Shapes/Containers,2,,,,,,,,_2Donor_sort.bam,,,,,,,
+22,Text,Standard,2,,,,,,,,index samtools index,,,,,,,
+23,Decision,Flowchart Shapes/Containers,2,,,,,,,,_2Donor_sort.bam.bai,,,,,,,
+24,Text,Standard,2,,,,,,,,calculate coverage with BedTools genomeCoverageBed,,,,,,,
+25,Decision,Flowchart Shapes/Containers,2,,,,,,,,coverage _2Donor_coverage.txt,,,,,,,
+26,Text,Standard,2,,,,,,,,Variant calling bcftools call,,,,,,,
+27,Decision,Flowchart Shapes/Containers,2,,,,,,,,variant list _2Ref_bcfcall.vcf,,,,,,,
+28,Display,Flowchart Shapes/Containers,2,,,,,,,,"paths, filenames, sampleType, filter parameters",,,,,,,
+29,Decision,Flowchart Shapes/Containers,2,,,,,,,,SNPSummary.mat,,,,,,,
+30,Text,Standard,2,,,,,,,,A0c_AccessoryGenome.m,,,,,,,
+31,Display,Flowchart Shapes/Containers,2,,,,,,,,"paths, filenames, filter parameters, genome length recipient (.fasta letter count AGTC)",,,,,,,
+32,Sticky note,Sticky Notes,2,,,,,,,,list of single replacements + some metadata,,,,,,,
+33,Sticky note,Sticky Notes,2,,,,,,,,filters single replacements,,,,,,,
+34,Sticky note,Sticky Notes,2,,,,,,,,list of single replacements + their positions -------------------  for each sample,,,,,,,
+35,Sticky note,Sticky Notes,2,,,,,,,,filters ???,,,,,,,
+36,Sticky note,Sticky Notes,2,,,,,,,,list of single replacements + their positions -------------------  for each sample,,,,,,,
+37,Cloud,Geometric Shapes,2,,,,,,,,2_CombiScript Samtools.sh,,,,,,,
+38,Decision,Flowchart Shapes/Containers,2,,,,,,,,.dict (recipient WT),,,,,,,
+39,Cloud,Geometric Shapes,2,,,,,,,,1_QCScript.sh,,,,,,,
+40,Decision,Flowchart Shapes/Containers,2,,,,,,,,raw reads .fastq(.gz) of donor,,,,,,,
+41,Decision,Flowchart Shapes/Containers,2,,,,,,,,(un)paired reads          _P.fastq          _U.fastq,,,,,,,
+42,Decision,Flowchart Shapes/Containers,2,,,,,,,,variant list _2Ref_bcf.vcf,,,,,,,
+43,Delete,Salesforce Architecture Diagrams,2,,,,,,,,,,,,,,,
+44,Decision,Flowchart Shapes/Containers,2,,,,,,,,.fasta        (donor),,,,,,,
+45,LinkUnfurlBlock,,2,,,,,,,,Basic Local Alignment Search Tool,Nih,,,,,,
+46,Text,Standard,2,,,,,,,,A0d_Multimapper.m,,,,,,,
+47,Text,Standard,2,,,,,,,,2x,,,,,,,
+48,Decision,Flowchart Shapes/Containers,2,,,,,,,,.fasta        (recipient WT),,,,,,,
+49,Decision,Flowchart Shapes/Containers,2,,,,,,,,.fasta        (recipient WT),,,,,,,
+50,Decision,Flowchart Shapes/Containers,2,,,,,,,,.fasta        (recipient WT),,,,,,,
+51,Decision,Flowchart Shapes/Containers,2,,,,,,,,.fasta        (donor),,,,,,,
+52,Decision,Flowchart Shapes/Containers,2,,,,,,,,hittable (text),,,,,,,
+53,Decision,Flowchart Shapes/Containers,2,,,,,,,,hitttable (text),,,,,,,
+54,Right arrow,Geometric Shapes,2,,,,,,,,"""simulates"" hybrid with 100% transfer",,,,,,,
+55,Decision,Flowchart Shapes/Containers,2,,,,,,,,mm_list.txt,,,,,,,
+56,Decision,Flowchart Shapes/Containers,2,,,,,,,,mm.txt,,,,,,,
+57,Text,Standard,2,,,,,,,,A0b_MasterListFiltering.m,,,,,,,
+58,Decision,Flowchart Shapes/Containers,2,,,,,,,,acc..._allBP.txt,,,,,,,
+59,Decision,Flowchart Shapes/Containers,2,,,,,,,,acc..._allBP.mat,,,,,,,
+60,Decision,Flowchart Shapes/Containers,2,,,,,,,,master list ml....mat,,,,,,,
+61,Decision,Flowchart Shapes/Containers,2,,,,,,,,master list  ml...txt,,,,,,,
+62,Text,Standard,2,,,,,,,,A1_SNP2CNP.m,,,,,,,
+63,Decision,Flowchart Shapes/Containers,2,,,,,,,,CNPSummary.mat,,,,,,,
+64,Cloud,Geometric Shapes,2,,,,,,,,2_CombiScript Samtools.sh,,,,,,,
+65,Decision,Flowchart Shapes/Containers,2,,,,,,,,.dict (recipient WT),,,,,,,
+66,Cloud,Geometric Shapes,2,,,,,,,,1_QCScript.sh,,,,,,,
+67,Decision,Flowchart Shapes/Containers,2,,,,,,,,raw reads .fastq(.gz) of recipient,,,,,,,
+68,Decision,Flowchart Shapes/Containers,2,,,,,,,,(un)paired reads          _P.fastq          _U.fastq,,,,,,,
+69,Decision,Flowchart Shapes/Containers,2,,,,,,,,SNP artefacts ReciWT_2Ref_ bcfcall.vcf,,,,,,,
+70,Right arrow,Geometric Shapes,2,,,,,,,,"""simulates"" hybrid with 0% transfer",,,,,,,
+71,DividerBlock,,2,,,,,,,,,,,,,,,
+72,Text,Standard,2,,,,,,,,Create dictionary picard.jar CreateSequenceDictionary,,,,,,,
+73,DividerBlock,,2,,,,,,,,,,,,,,,
+74,Text,Standard,2,,,,,,,,2x,,,,,,,
+75,Text,Standard,2,,,,,,,,A0_VariantFiltering.m,,,,,,,
+76,Decision,Flowchart Shapes/Containers,2,,,,,,,,SNP artefact list _ArteSNPs.mat,,,,,,,
+77,Delete,Salesforce Architecture Diagrams,2,,204,,,,,,,,,,,,,
+78,Text,Standard,2,,204,,,,,,"bcf, sam, bam",,,,,,,
+79,Delete,Salesforce Architecture Diagrams,2,,205,,,,,,,,,,,,,
+80,Text,Standard,2,,205,,,,,,"bcfcall, sam, bam, txt",,,,,,,
+81,Decision,Flowchart Shapes/Containers,2,,,,,,,,(un)paired reads        _P.fastq _U.fastq,,,,,,,
+82,Text,Standard,2,,,,,,,,"A3_Cov2DelDup.m
+finds deletions + duplications     based on coverage",,,,,,,
+83,Sticky note,Sticky Notes,2,,,,,,,,how frequently a certain locus was read,,,,,,,
+84,Decision,Flowchart Shapes/Containers,2,,206,,,,,,,,,,,,,
+85,Decision,Flowchart Shapes/Containers,2,,206,,,,,,,,,,,,,
+86,Decision,Flowchart Shapes/Containers,2,,206,,,,,,(un)paired reads        _P.fastq _U.fastq,,,,,,,
+87,Decision,Flowchart Shapes/Containers,2,,,,,,,,artefacts _ArteCov.txt,,,,,,,
+88,Decision,Flowchart Shapes/Containers,2,,,,,,,,_DelDup _sample.mat,,,,,,,
+89,Text,Standard,2,,,,,,,,"A4_Cov2Ins.m
+finds insertions based on coverage",,,,,,,
+90,Decision,Flowchart Shapes/Containers,2,,,,,,,,AccMM2Genes.mat,,,,,,,
+91,Sticky note,Sticky Notes,2,,,,,,,,"Load existing .mat and empty all cells (empty_AccMM2Genes.mat). Run A2_List2Genes.m in txtListStartEnd-mode with acc..._allBP.txt as far as possible, skip/fix possible errors until MultiHitStat is generated. Save as .mat and filter for FracMean > 0 (e.g. use FilterStructArray_by_PH.m). ",,,,,,,
+92,Text,Standard,2,,,,,,,,A2_List2Genes.m,,,,,,,
+93,Decision,Flowchart Shapes/Containers,2,,,,,,,,bed file ...bed.mat,,,,,,,
+94,Cloud Deployment Manager,Google Cloud Platform 2021,2,,,,,,,,plots,,,,,,,
+95,Decision,Flowchart Shapes/Containers,2,,,,,,,,.dict (recipient WT),,,,,,,
+96,Decision,Flowchart Shapes/Containers,2,,,,,,,,.dict (donor),,,,,,,
+97,Decision,Flowchart Shapes/Containers,2,,,,,,,,_2Ref.sam,,,,,,,
+98,Text,Standard,2,,,,,,,,sort samtools sort,,,,,,,
+99,Decision,Flowchart Shapes/Containers,2,,,,,,,,_2Ref_sort.bam,,,,,,,
+100,Text,Standard,2,,,,,,,,index samtools index,,,,,,,
+101,Decision,Flowchart Shapes/Containers,2,,,,,,,,_2Ref_sort.bam.bai,,,,,,,
+102,Display,Flowchart Shapes/Containers,2,,,,,,,,"paths, filenames, filter parameters, genome length recipient (.fasta letter count AGTC)",,,,,,,
+103,Cloud Deployment Manager,Google Cloud Platform 2021,2,,,,,,,,plots,,,,,,,
+104,Display,Flowchart Shapes/Containers,2,,,,,,,,"paths, filenames, filter parameters, genome length recipient (.fasta letter count AGTC)",,,,,,,
+105,Diagram key,Standard,2,,,,,,,,Legend,recipient file,donor file,reciprocal hybrid (recipient/donor) file,hybrid (donor/recipient) file,Matlab program (.m) or bash command,bash file,
+106,Line,,2,,,8,72,None,Arrow,,,,,,,,,
+107,Line,,2,,,72,95,None,Arrow,,,,,,,,,
+108,Line,,2,,,10,9,None,Arrow,,,,,,,,,
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+128,Line,,2,,,24,25,None,Arrow,,,,,,,,,
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+140,Line,,2,,,27,75,None,Arrow,,,,,,,,,
+141,Line,,2,,,75,29,None,Arrow,,,,,,,,,
+142,Line,,2,,,31,30,None,Arrow,,,,,,,,,
+143,Line,,2,,,,,None,None,,,,,,,,,
+144,Line,,2,,,40,39,None,Arrow,,,,,,,,,
+145,Line,,2,,,39,41,None,Arrow,,,,,,,,,
+146,Line,,2,,,41,37,None,Arrow,,,,,,,,,
+147,Line,,2,,,38,37,None,Arrow,,,,,,,,,
+148,Line,,2,,,37,42,None,Arrow,,,,,,,,,
+149,Line,,2,,,42,30,None,Arrow,,,,,,,,,
+150,Line,,2,,,21,43,None,Arrow,,,,,,,,,
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+157,Line,,2,,,48,45,None,Arrow,,subject,,,,,,,
+158,Line,,2,,,49,45,None,Arrow,,query,,,,,,,
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+197,Line,,2,,,95,38,None,None,,,,,,,,,
+198,Line,,2,,,102,82,None,Arrow,,,,,,,,,
+199,Line,,2,,,25,89,None,Arrow,,,,,,,,,
+200,Line,,2,,,82,103,None,Arrow,,,,,,,,,
+201,Line,,2,,,58,89,None,Arrow,,???,,,,,,,
+202,Line,,2,,,104,89,None,Arrow,,,,,,,,,
+203,Line,,2,,,95,65,None,None,,,,,,,,,
+204,Group 1,,2,,,,,,,,,,,,,,,
+205,Group 2,,2,,,,,,,,,,,,,,,
+206,Group 3,,2,,,,,,,,,,,,,,,
\ No newline at end of file
diff --git a/documentation/DetectionGV.pdf b/documentation/DetectionGV.pdf
new file mode 100644
index 0000000..1e14c77
Binary files /dev/null and b/documentation/DetectionGV.pdf differ
diff --git a/documentation/DetectionGV.png b/documentation/DetectionGV.png
new file mode 100644
index 0000000..bd0c261
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diff --git a/documentation/DetectionGV.svg b/documentation/DetectionGV.svg
new file mode 100644
index 0000000..12ba0c7
--- /dev/null
+++ b/documentation/DetectionGV.svg
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" 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+The diagram was created with LucidChart. Unfortunately this is closed and some featurs are premium only, so it is a kind of vendor lock-in. I can share the diagram to your LucidChart account, otherwise feel free to rebuild it from the given files.
+<https://lucid.app/documents/view/fa9f52da-edf4-4fb2-9b6c-d01996f4768e>
+
+ <p xmlns:cc="http://creativecommons.org/ns#" >This diagram is marked with <a href="http://creativecommons.org/publicdomain/zero/1.0?ref=chooser-v1" target="_blank" rel="license noopener noreferrer" style="display:inline-block;">CC0 1.0<img style="height:22px!important;margin-left:3px;vertical-align:text-bottom;" src="https://mirrors.creativecommons.org/presskit/icons/cc.svg?ref=chooser-v1"><img style="height:22px!important;margin-left:3px;vertical-align:text-bottom;" src="https://mirrors.creativecommons.org/presskit/icons/zero.svg?ref=chooser-v1"></a> and dedicated to the public domain.</p>