Merge pull request #61 from TASBE/coverney.issue410

Created the batch_template_csv file

.travis.yml

@@ -45,7 +45,7 @@ before_install:
     - make -C MOdox install
     # retrieve TASBE for running tests
     - rm -rf TASBEFlowAnalytics
-    - git clone --branch=master  https://github.com/TASBE/TASBEFlowAnalytics 
+    - git clone --branch=develop  https://github.com/TASBE/TASBEFlowAnalytics 
     - make -C TASBEFlowAnalytics install
     # go back to original directory
     - cd TASBEFlowAnalytics-Tutorial

template_analysis/batch_template_csv.m

@@ -0,0 +1,68 @@
+% This template shows how to perform a simple batch analysis of a set of conditions
+% Each color is analyzed independently
+TASBEConfig.checkpoint(TASBEConfig.checkpoints());
+
+% load the color model
+load('../template_colormodel/CM120312.mat');
+% can also add filters, such as gating out all "low transfection" red less than 10^6 MEFL:
+%CM = add_postfilter(CM,RangeFilter('PE-Tx-Red-YG-A',[1e6 inf]));
+
+
+% set up metadata
+experimentName = 'LacI Transfer Curve';
+
+% Configure the analysis
+% Analyze on a histogram of 10^[first] to 10^[third] ERF, with bins every 10^[second]
+bins = BinSequence(4,0.1,10,'log_bins');
+
+% Designate which channels have which roles
+AP = AnalysisParameters(bins,{});
+% Ignore any bins with less than valid count as noise
+AP=setMinValidCount(AP,100');
+% Ignore any raw fluorescence values less than this threshold as too contaminated by instrument noise
+AP=setPemDropThreshold(AP,5');
+% Add autofluorescence back in after removing for compensation?
+AP=setUseAutoFluorescence(AP,false');
+% By default, analysis tries to fit constitutive to transformed and non-transformed components
+% If your distribution is more complex or less complex, you can change the number of components
+% AP=setNumGaussianComponents(AP,3);
+
+% Make a map of condition names to file sets
+stem1011 = 'csv/LacI-CAGop_Dox';
+root1011 = '_PointCloud.csv';
+file_pairs = {...
+  'Dox 0.1',    {[stem1011 '01' root1011]}; % Replicates go here, e.g., {[rep1], [rep2], [rep3]}
+  'Dox 0.2',    {[stem1011 '02' root1011]};
+  'Dox 0.5',    {[stem1011 '05' root1011]};
+  'Dox 1.0',    {[stem1011 '1' root1011]};
+  'Dox 2.0',    {[stem1011 '2' root1011]};
+  'Dox 5.0',    {[stem1011 '5' root1011]};
+  'Dox 10.0',   {[stem1011 '10' root1011]};
+  'Dox 20.0',   {[stem1011 '20' root1011]};
+  'Dox 50.0',   {[stem1011 '50' root1011]};
+  'Dox 100.0',  {[stem1011 '100' root1011]};
+  'Dox 200.0',  {[stem1011 '200' root1011]};
+  'Dox 500.0',  {[stem1011 '500' root1011]};
+  'Dox 1000.0', {[stem1011 '1000' root1011]};
+  'Dox 2000.0', {[stem1011 '2000' root1011]};
+  };
+
+n_conditions = size(file_pairs,1);
+
+% Execute the actual analysis
+TASBEConfig.set('OutputSettings.StemName','LacI-CAGop');
+TASBEConfig.set('OutputSettings.FixedInputAxis',[1e4 1e10]);
+% Set CSVReaderHeader (temporary feature)
+TASBEConfig.set('flow.defaultCSVReadHeader','csv/LacI-CAGop.json');
+% Generate point cloud csv files
+%TASBEConfig.set('flow.outputPointCloud', true);
+[results, sampleresults] = per_color_constitutive_analysis(CM,file_pairs,{'EYFP','mKate', 'EBFP2'},AP);
+
+% Make output plots
+plot_batch_histograms(results,sampleresults,CM); % linespecs obtained from CM
+% can enter own linespecs for plot_batch_histograms:
+% plot_batch_histograms(results,sampleresults,CM,{'b','g','r'});
+
+[statisticsFile, histogramFile] = serializeBatchOutput(file_pairs, CM, AP, sampleresults);
+
+save('LacI-CAGop-batch.mat','AP','bins','file_pairs','results','sampleresults');

template_analysis/csv/LacI-CAGop.json

@@ -0,0 +1,27 @@
+[
+	3,
+	"FITC-A",
+	"PE-Tx-Red-YG-A",
+	"Pacific Blue-A",
+	"EYFP",
+	"mKate",
+	"EBFP2",
+	"ERF",
+	"ERF",
+	"ERF",
+	14,
+	"csv\/LacI-CAGop_Dox01_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox02_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox05_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox1_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox2_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox5_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox10_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox20_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox50_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox100_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox200_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox500_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox1000_PointCloud.csv",
+	"csv\/LacI-CAGop_Dox2000_PointCloud.csv"
+]