source: prdatasets/flowcyto.m @ 148

Last change on this file since 148 was 142, checked in by bduin, 5 years ago

Updated collection of datasets

File size: 2.0 KB
Line 
1%FLOWCYTO Load 4 flow-cytometry datasets.
2%
3%   A = FLOWCYTO(N)
4%
5% These datasets are based on 612 FL3-A DNA flowcytometer histograms
6% from breast cancer tissues in 256 resolution. The initial data have been
7% acquired by M. Nap and N. van Rodijnen of the Atrium Medical Center in
8% Heerlen, The Netherlands, during 2000-2004, using tubes 3-6 of a DACO
9% Galaxy flowcytometer (N = 1-4). Histograms are labeled in 3 classes:
10% aneuploid (335 patients), diploid (131) and tetraploid (146). The first
11% and the last bin (1 and 256) are set to 0, as they contsin noise. After
12% that histograms are normalized (sum to one) resulting in a dataset with
13% 254 features.
14%
15% The four datasets are aligned for the same patients, but are based on
16% different measurements.
17%
18% SEE ALSO
19% PRTOOLS, DATASETS
20
21% Copyright: R.P.W. Duin, r.p.w.duin@37steps.com
22
23
24function a = flowcyto(n)
25
26if nargin < 1 || isempty(n)
27  n = 1;
28end
29
30if any(n<1) || any(n>4)
31  error('Dataset number should be larger than 0 and smaller than 5')
32end
33
34d = pr_getdata('http://37steps.com/data/prdatasets/FlowCyto_sort.mat',5);
35
36a = cell(1,numel(n));
37for j=1:numel(n)
38  x = prdataset(d{n(j)});
39  x = setname(x(:,2:255),['Flow Cytometry ' num2str(n(j))]);
40  desc = ['These datasets are based on 612 FL3-A DNA flowcytometer histograms' ...
41  'from breast cancer tissues in 256 resolution. The initial data have been' ...
42  'acquired by M. Nap and N. van Rodijnen of the Atrium Medical Center in' ...
43  'Heerlen, The Netherlands, during 2000-2004, using tubes 3-6 of a DACO' ...
44  'Galaxy flowcytometer (N = 1-4). Histograms are labeled in 3 classes:' ...
45  'aneuploid (335 patients), diploid (131) and tetraploid (146). The first' ...
46  'and the last bin (1 and 256) are set to 0, as they contsin noise. After' ...
47  'that histograms are normalized (sum to one) resulting in a dataset with' ...
48  '254 features.'];
49  ref = {['']};
50  x = setprior(x,getprior(x,0));
51  x = setuser(x,desc,'desc');
52  x = setuser(x,ref,'ref');
53  a{j} = x;
54end
55
56if numel(a) == 1
57  a = a{1};
58end
59
60
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