Research Article
A Fast Cluster Motif Finding Algorithm for ChIP-Seq Data Sets
Table 2
An example of searching the neighbourhood instances of a reference
-mer.
| | Reference -mer: ACCACGTG (, ) = (8, 1) = 19.36 = 119 = 9 | | Position | Instance | | | | Position | Instance | | | |
| | CCCACGTG | 21.78 | 146 | 11 | | AACACGTG | 11.83 | 51 | 5 | | GCCACGTG | 26.14 | 177 | 7 | AGCACGTG | 22.66 | 149 | 9 | | TCCACGTG | 15.93 | 91 | 9 | ATCACGTG | 3.28 | 16 | 6 |
| | ACAACGTG | 2.38 | 9 | 4 | | ACCCCGTG | 2.88 | 15 | 6 | | ACGACGTG | 1.82 | 7 | 3 | ACCGCGTG | 8.23 | 25 | 3 | | ACTACGTG | 1.31 | 5 | 3 | ACCTCGTG | 6.16 | 23 | 5 |
| | ACCAAGTG | −0.73 | 7 | 9 | | ACCACATG | 0.14 | 27 | 26 | | ACCAGGTG | −0.12 | 14 | 14 | ACCACCTG | −0.30 | 17 | 18 | | ACCATGTG | 2.88 | 48 | 30 | ACCACTTG | −2.08 | 2 | 8 |
| | ACCACGAG | 5.92 | 24 | 5 | | ACCACGTA | −0.07 | 3 | 3 | | ACCACGCG | 8.63 | 30 | 4 | ACCACGTC | 1.03 | 7 | 5 | | ACCACGGG | 3.53 | 14 | 5 | ACCACGTT | −0.05 | 4 | 4 |
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