Estimation of the methylation pattern distribution from deep sequencing data

BMC Bioinformatics

Table 2 Estimated methylation distribution \( {\widehat{\theta}}_i \) for the data of Figure 5

i	m _i	y _i	y _i / N _read	\( {\widehat{\theta}}_i \)
1	00000000	1265	0.7055	0.8706
2	00000001	52	0.0290	0.0059
3	00000010	32	0.0178	0
4	00000100	40	0.0223	0
5	00000110	3	0.0017	0.0010
6	00001000	75	0.0418	0.0189
7	00001001	1	0.0006	0
8	00001010	2	0.0011	0
9	00010000	36	0.0201	0
10	00010100	10	0.0056	0.0053
11	00100000	31	0.0173	0
12	00100001	2	0.0011	0.0003
13	00101000	1	0.0006	0
14	00110000	1	0.0006	0
15	01000000	20	0.0112	0
16	01000001	1	0.0006	0
17	01100000	39	0.0218	0.0240
18	01100001	4	0.0022	0.0016
19	01101000	1	0.0006	0
20	01110000	1	0.0006	0
21	01110100	1	0.0006	0
22	10000000	84	0.0468	0.0282
23	10000001	2	0.0011	0
24	10000010	5	0.0028	0.0013
25	10000100	14	0.0078	0.0070
26	10001000	1	0.0006	0
27	10010000	2	0.0011	0
28	10010100	8	0.0045	0.0044
29	10100000	2	0.0011	0
30	11000100	1	0.0006	0.0003
31	11010000	1	0.0006	0.0005
32	11100000	1	0.0006	0
33	11100100	2	0.0011	0.0006
34	11110000	2	0.0011	0.0007
35	11110100	42	0.0234	0.0255
36	11110110	8	0.0045	0.0039

The 36 patterns with non-zero reads are labelled m _i, i=1,…,36 and y _i are the observed read counts.

ISSN: 1471-2105