Merge pull request #1 from jakebeal/master

pull updated examples and FCS files

01_flow_cytometry/exercises.m

@@ -2,23 +2,23 @@
 % Preliminaries: set up TASBE analytics package:
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
-% addpath('~/cur_proj/SynBioIRAD/TASBE_Analytics/');
+% example: addpath('~/Downloads/TASBEFlowAnalytics/');
 addpath('your-path-to-analytics');
 % turn off sanitized filename warnings:
 warning('off','TASBE:SanitizeName');
 
-colordata = '../../colortest/';
-dosedata = '../../plasmidtest/';
+colordata = '../example_controls/';
+dosedata = '../example_assay/';
 
 
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 % Examples of flow data
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% pure scatter
+% pure scatter - often hard to interpret
 fcs_scatter([dosedata 'LacI-CAGop_C4_C04_P3.fcs'],'PE-Tx-Red-YG-A','Pacific Blue-A',0,[0 0; 6 6],1);
 fcs_scatter([colordata '07-29-11_EYFP_P3.fcs'],'FITC-A','Pacific Blue-A',0,[0 0; 6 6],1);
-% smoothed density plot
+% smoothed density plot omits details but often summarizes collective better
 data1 = fcs_scatter([dosedata 'LacI-CAGop_C4_C04_P3.fcs'],'PE-Tx-Red-YG-A','Pacific Blue-A',1,[0 0; 6 6],1);
 data2 = fcs_scatter([colordata '07-29-11_EYFP_P3.fcs'],'FITC-A','Pacific Blue-A',1,[0 0; 6 6],1);
 
@@ -68,15 +68,16 @@
 
 data(data(:,7)>260000,7)
 % ans = 262143
-% How high was this really?  We cannot know...
+% How high was this really?  We cannot know because it is saturated!
 
 
 
 
 channels = {};
-channels{1} = Channel('', 'Pacific Blue-A', '',234,456);
-channels{2} = Channel('', 'PE-Tx-Red-YG-A', '',890,123);
-channels{3} = Channel('', 'FITC-A', '',789,345);
+
+channels{1} = Channel('Pacific Blue-A', 405, 450, 50);
+channels{2} = Channel('PE-Texas Red-A', 561, 610, 20);
+channels{3} = Channel('FITC-A', 488, 530, 30);
 CM = ColorModel('','',channels,{{},{},{}},{});
 
 filtered = read_filtered_au(CM,[colordata '07-29-11_EYFP_P3.fcs']);
@@ -88,4 +89,4 @@
 xc = dequantized(:,10); yc = dequantized(:,11);
 pos = xc>0 & yc>0;
 figure; smoothhist2D(log10([xc(pos) yc(pos)]),10,[200, 200],[],'image',[0 0; 6 6]);
-% quantization gets smoothed out by introduction of small noise
+% if desired, quantization can be smoothed out by introduction of small noise

02_flow_compensation/exercises.m

@@ -2,13 +2,13 @@
 % Preliminaries: set up TASBE analytics package:
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
-% addpath('~/cur_proj/SynBioIRAD/TASBE_Analytics/');
+% example: addpath('~/Downloads/TASBEFlowAnalytics/');
 addpath('your-path-to-analytics');
 % turn off sanitized filename warnings:
 warning('off','TASBE:SanitizeName');
 
-colordata = '../../colortest/';
-dosedata = '../../plasmidtest/';
+colordata = '../example_controls/';
+dosedata = '../example_assay/';
 
 
 
@@ -38,17 +38,23 @@
 [raw hdr data] = fca_readfcs([colordata '07-29-11_blank_P3.fcs']);
 % histogram of EBFP2:
 figure; hist(data(:,10),100);
-% with randomization:
+% with random blurring to damp quanization:
 figure; hist(data(:,10)+(rand(size(data(:,10)))-0.5),100);
 % Notice that the presence of negative values means that we are necessarily dealing with a combination
-% of autofluorescence and read error.  We currently don't know how to separate these from one another.
+% of autofluorescence and instrument error.  There is not currently any elegant way of separating these.
 
 % fit to a gaussian model:
-mean(data(:,10))
-std(data(:,10))
+mu = mean(data(:,10))
+sigma = std(data(:,10))
+
+% Notice that the fit is pretty good:
+range = -100:5:150;
+figure;
+plot(range,histc(data(:,10),range),'b-'); hold on;
+plot(range,numel(data(:,10))*5*normpdf(range,mu,sigma),'r--');
 
 
-% we can simulate a distribution as a sum of three terms: random (bled) signal, autofluorescence, and read error
+% we can simulate a distribution as a sum of three terms: random (bleed) signal, autofluorescence, and read error
 % here are some arbitrary values to explore as an example:
 n = 1e5; 
 signal = 10.^(randn(n,1)*1+2.5);
@@ -85,24 +91,25 @@
 blankfile = [colordata '2012-03-12_blank_P3.fcs'];
 
 channels = {}; colorfiles = {};
-channels{1} = Channel('Pacific Blue-A', 405,0,0);
+channels{1} = Channel('Pacific Blue-A', 405,450,50);
 channels{1} = setPrintName(channels{1},'Blue');
 colorfiles{1} = [colordata '2012-03-12_ebfp2_P3.fcs'];
 channels{2} = Channel('PE-Tx-Red-YG-A', 561,610,20);
 channels{2} = setPrintName(channels{2},'Red');
 colorfiles{2} = [colordata '2012-03-12_mkate_P3.fcs'];
-channels{3} = Channel('FITC-A', 488,515,20);
+channels{3} = Channel('FITC-A', 488,530,30);
 channels{3} = setPrintName(channels{3},'Yellow');
 colorfiles{3} = [colordata '2012-03-12_EYFP_P3.fcs'];
 
 colorpairfiles = {};
 CM = ColorModel(beadfile, blankfile, channels, colorfiles, colorpairfiles);
+CM = set_FITC_channel_name(CM, 'FITC-A'); % We'll explain this in the next exercise
 settings = TASBESettings();
 
 % Now let's read some files...
 raw = read_filtered_au(CM,[dosedata 'LacI-CAGop_C3_C03_P3.fcs']);
 compensated = readfcs_compensated_au(CM,[dosedata 'LacI-CAGop_C3_C03_P3.fcs'],0,1);
-% oops!  Need to resolve our color model first!
+% You should see an error: need to "resolve" the color model first!
 
 CM = resolve(CM,settings);
 
@@ -163,11 +170,3 @@
 
 % An important question for the future:
 % We need to be able to set error bars on the data points that we correct.  Can we?
-
-
-
-
-
-
-
-

03_flow_MEFL/exercises.m

@@ -2,20 +2,20 @@
 % Preliminaries: set up TASBE analytics package:
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
-% addpath('~/cur_proj/SynBioIRAD/TASBE_Analytics/');
+% example: addpath('~/Downloads/TASBEFlowAnalytics/');
 addpath('your-path-to-analytics');
 % turn off sanitized filename warnings:
 warning('off','TASBE:SanitizeName');
 
-colordata = '../../colortest/';
-dosedata = '../../plasmidtest/';
+colordata = '../example_controls/';
+dosedata = '../example_assay/';
 
 
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 % Calibration beads:
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% Let's look at an example of RCP-30-5A calibration beads:
+% Let's look at an example of SpheroTech RCP-30-5A calibration beads:
 fcs_scatter([colordata '2012-03-12_Beads_P3.fcs'],'Pacific Blue-A','PE-Tx-Red-YG-A',1,[0 0; 6 6],1);
 % and without blending...
 fcs_scatter([colordata '2012-03-12_Beads_P3.fcs'],'Pacific Blue-A','PE-Tx-Red-YG-A',0,[0 0; 6 6],1);
@@ -52,13 +52,13 @@
 blankfile = [colordata '2012-03-12_blank_P3.fcs'];
 
 channels = {}; colorfiles = {};
-channels{1} = Channel('Pacific Blue-A', 405,0,0);
+channels{1} = Channel('Pacific Blue-A', 405,450,50);
 channels{1} = setPrintName(channels{1},'Blue');
 colorfiles{1} = [colordata '2012-03-12_ebfp2_P3.fcs'];
 channels{2} = Channel('PE-Tx-Red-YG-A', 561,610,20);
 channels{2} = setPrintName(channels{2},'Red');
 colorfiles{2} = [colordata '2012-03-12_mkate_P3.fcs'];
-channels{3} = Channel('FITC-A', 488,515,20);
+channels{3} = Channel('FITC-A', 488,530,30);
 channels{3} = setPrintName(channels{3},'Yellow');
 colorfiles{3} = [colordata '2012-03-12_EYFP_P3.fcs'];
 
@@ -69,6 +69,7 @@
 
 CM = ColorModel(beadfile, blankfile, channels, colorfiles, colorpairfiles);
 settings = TASBESettings();
+CM = set_FITC_channel_name(CM, 'FITC-A'); % Name the channel we'll use for MEFL units
 CM=set_dequantization(CM, 1); % important at low levels
 CM=set_bead_plot(CM, 2); % 2 = show beads for all channels, even though only FITC will be used
 CM=set_bead_min(CM, 1); % Don't consider beads less than this amount

README.md

@@ -6,3 +6,8 @@ This tutorial has three units:
 1. How Flow Cytometry Works
 2. Autofluorescence and Compensation in Cells
 3. From Arbitrary to Absolute Units
+
+Example code in this tutorial is distributed, insofar as possible, in
+the public domain.
+
+Example flow cytometry files are provided courtesy of Prof. Ron Weiss (MIT).