Supplementary file S08. Test partitioning methods


In the process of recursively splitting the similarity matrix in binary cut algorithm, in each iteration step, the current matrix is partitioned into two groups using PAM as default. Here we compare following partitioning methds: k-means, PAM and hierarchical clustering with methods of 'complete', 'average' and 'ward.D2', on 500 random GO lists.

Figure S8.1.Compare clustering results. Left panel: The difference score, number of clusters and the block mean of different clusterings. Right panel: Concordance between clustering methods. The concordance measures how similar two clusterings are. The definition of the concordance score can be found here.

Table S8.1.Number of clusters identified by each clustering method. Numbers in the table indicate the number of clusters. The numbers inside the parentheses are the number of clusters with size >= 5.

run partition_by_kmeans partition_by_pam partition_by_hclust_complete partition_by_hclust_ward.D2 partition_by_hclust_average Details
1 47 (9) 38 (7) 41 (12) 34 (6) 37 (7) view
2 32 (9) 27 (5) 32 (8) 31 (10) 32 (9) view
3 43 (10) 42 (12) 46 (13) 41 (12) 44 (13) view
4 41 (9) 38 (6) 40 (14) 38 (10) 37 (12) view
5 42 (12) 36 (11) 35 (11) 30 (9) 33 (10) view
6 38 (7) 40 (10) 38 (10) 36 (9) 38 (10) view
7 31 (10) 31 (11) 31 (11) 27 (8) 27 (10) view
8 38 (9) 36 (9) 35 (9) 35 (9) 35 (12) view
9 46 (9) 39 (11) 40 (13) 39 (11) 38 (11) view
10 37 (9) 37 (8) 40 (13) 35 (8) 38 (8) view
11 52 (12) 41 (9) 39 (15) 36 (9) 38 (10) view
12 43 (9) 41 (11) 40 (10) 40 (9) 39 (9) view
13 34 (12) 30 (10) 33 (10) 30 (8) 33 (11) view
14 45 (8) 36 (9) 35 (10) 33 (9) 34 (9) view
15 49 (8) 42 (10) 41 (12) 38 (10) 40 (9) view
16 45 (9) 36 (12) 36 (12) 33 (12) 34 (12) view
17 49 (16) 44 (13) 45 (13) 42 (12) 43 (13) view
18 39 (10) 40 (9) 41 (14) 36 (10) 43 (15) view
19 40 (9) 40 (10) 42 (14) 35 (8) 37 (9) view
20 44 (9) 38 (9) 39 (9) 37 (8) 41 (8) view
21 48 (12) 40 (10) 40 (12) 38 (10) 38 (9) view
22 36 (10) 37 (11) 34 (9) 35 (12) 36 (12) view
23 37 (7) 33 (8) 35 (10) 31 (9) 32 (10) view
24 44 (11) 40 (10) 35 (12) 34 (10) 37 (11) view
25 46 (8) 42 (9) 43 (11) 40 (11) 43 (13) view
26 43 (9) 41 (9) 47 (13) 38 (5) 43 (10) view
27 39 (11) 38 (10) 39 (11) 37 (10) 38 (10) view
28 52 (15) 37 (13) 41 (16) 37 (13) 37 (14) view
29 38 (10) 37 (13) 39 (11) 33 (9) 37 (12) view
30 36 (6) 35 (8) 33 (8) 32 (7) 32 (7) view
31 47 (9) 41 (11) 42 (14) 36 (9) 38 (9) view
32 38 (8) 42 (9) 40 (11) 36 (7) 40 (8) view
33 37 (8) 38 (9) 37 (11) 36 (10) 36 (10) view
34 39 (11) 34 (10) 28 (9) 27 (9) 31 (9) view
35 38 (11) 38 (9) 38 (9) 32 (7) 38 (9) view
36 38 (11) 33 (9) 32 (9) 32 (8) 32 (9) view
37 52 (15) 48 (11) 48 (13) 45 (11) 47 (11) view
38 32 (11) 28 (16) 32 (17) 25 (12) 24 (12) view
39 42 (12) 41 (12) 40 (11) 37 (12) 41 (12) view
40 44 (6) 39 (9) 41 (12) 36 (8) 38 (10) view
41 37 (8) 36 (9) 36 (10) 34 (9) 0 (0) view
42 28 (7) 33 (12) 28 (9) 28 (7) 29 (9) view
43 41 (13) 34 (10) 35 (9) 35 (9) 37 (10) view
44 35 (13) 31 (10) 36 (11) 31 (9) 30 (9) view
45 48 (10) 42 (9) 43 (9) 39 (7) 41 (7) view
46 40 (7) 38 (8) 38 (10) 37 (7) 39 (9) view
47 44 (10) 37 (8) 37 (9) 35 (9) 37 (10) view
48 34 (10) 31 (7) 32 (10) 31 (8) 31 (10) view
49 37 (10) 29 (9) 32 (10) 33 (10) 33 (9) view
50 37 (9) 39 (10) 38 (10) 34 (9) 37 (10) view
51 42 (8) 37 (10) 41 (12) 38 (10) 39 (10) view
52 35 (11) 30 (11) 28 (11) 28 (10) 30 (10) view
53 45 (8) 43 (8) 41 (10) 41 (9) 40 (10) view
54 41 (7) 39 (10) 42 (13) 38 (9) 37 (9) view
55 50 (15) 37 (14) 36 (14) 33 (12) 35 (13) view
56 46 (11) 36 (9) 38 (14) 35 (8) 35 (10) view
57 42 (8) 35 (10) 35 (11) 33 (9) 31 (8) view
58 30 (9) 29 (10) 31 (10) 29 (10) 29 (9) view
59 37 (12) 34 (11) 34 (9) 35 (8) 34 (10) view
60 37 (9) 35 (8) 36 (10) 35 (7) 37 (8) view
61 46 (11) 40 (11) 39 (12) 39 (13) 39 (12) view
62 38 (11) 35 (11) 34 (10) 35 (10) 38 (11) view
63 38 (14) 34 (10) 32 (8) 31 (8) 33 (8) view
64 46 (9) 41 (9) 41 (9) 39 (8) 40 (8) view
65 42 (10) 36 (6) 42 (12) 36 (9) 36 (9) view
66 39 (9) 35 (7) 37 (10) 33 (9) 0 (0) view
67 39 (9) 33 (10) 37 (11) 32 (9) 34 (10) view
68 45 (9) 38 (11) 36 (10) 36 (10) 37 (10) view
69 39 (9) 31 (11) 31 (11) 30 (9) 28 (9) view
70 35 (8) 32 (11) 33 (11) 30 (9) 32 (11) view
71 22 (6) 32 (10) 33 (9) 34 (10) 35 (11) view
72 35 (10) 34 (10) 33 (12) 33 (10) 34 (10) view
73 54 (11) 42 (8) 44 (13) 39 (10) 39 (9) view
74 43 (15) 34 (12) 35 (12) 34 (10) 36 (11) view
75 36 (9) 36 (8) 37 (14) 33 (11) 33 (9) view
76 47 (7) 44 (7) 43 (9) 43 (8) 43 (9) view
77 39 (7) 39 (9) 41 (11) 41 (11) 43 (10) view
78 36 (10) 32 (8) 30 (8) 30 (9) 32 (8) view
79 44 (10) 39 (8) 38 (8) 37 (7) 38 (9) view
80 39 (9) 34 (6) 42 (12) 40 (12) 39 (10) view
81 47 (11) 47 (11) 47 (12) 43 (8) 47 (12) view
82 46 (13) 42 (12) 40 (10) 41 (10) 41 (10) view
83 33 (8) 32 (9) 34 (8) 30 (8) 33 (9) view
84 37 (10) 36 (10) 36 (9) 35 (9) 35 (10) view
85 43 (9) 41 (11) 37 (13) 34 (8) 35 (10) view
86 36 (8) 34 (10) 35 (13) 30 (9) 34 (10) view
87 39 (8) 38 (10) 37 (11) 35 (9) 38 (11) view
88 29 (6) 32 (10) 32 (12) 30 (9) 29 (10) view
89 37 (9) 34 (9) 35 (11) 33 (10) 33 (9) view
90 48 (11) 42 (11) 39 (8) 42 (10) 39 (8) view
91 40 (8) 41 (9) 38 (9) 39 (10) 38 (9) view
92 31 (11) 31 (11) 32 (12) 29 (8) 31 (10) view
93 36 (10) 35 (9) 36 (10) 34 (9) 35 (9) view
94 36 (12) 36 (13) 37 (13) 35 (12) 36 (10) view
95 44 (12) 34 (9) 41 (15) 39 (12) 39 (12) view
96 47 (13) 40 (10) 42 (11) 37 (6) 40 (8) view
97 45 (9) 35 (10) 38 (12) 34 (9) 34 (9) view
98 38 (10) 32 (11) 31 (11) 30 (11) 33 (11) view
99 33 (9) 36 (9) 37 (10) 33 (6) 32 (8) view
100 39 (9) 40 (10) 41 (12) 42 (11) 40 (10) view