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Comparative Study
. 2005 Mar 10;33(5):1445-53.
doi: 10.1093/nar/gki282. Print 2005.

NestedMICA: sensitive inference of over-represented motifs in nucleic acid sequence

Thomas A Down  1 , Tim J P Hubbard
Affiliations
Comparative Study

NestedMICA: sensitive inference of over-represented motifs in nucleic acid sequence

Thomas A Down et al. Nucleic Acids Res. .

Abstract

NestedMICA is a new, scalable, pattern-discovery system for finding transcription factor binding sites and similar motifs in biological sequences. Like several previous methods, NestedMICA tackles this problem by optimizing a probabilistic mixture model to fit a set of sequences. However, the use of a newly developed inference strategy called Nested Sampling means NestedMICA is able to find optimal solutions without the need for a problematic initialization or seeding step. We investigate the performance of NestedMICA in a range scenario, on synthetic data and a well-characterized set of muscle regulatory regions, and compare it with the popular MEME program. We show that the new method is significantly more sensitive than MEME: in one case, it successfully extracted a target motif from background sequence four times longer than could be handled by the existing program. It also performs robustly on synthetic sequences containing multiple significant motifs. When tested on a real set of regulatory sequences, NestedMICA produced motifs which were good predictors for all five abundant classes of annotated binding sites.

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Figures

Figure 1
Figure 1
The zero-or-one occurrences per sequence (ZOOPS) sequence mixture model (SMM), represented as a hidden Markov model (HMM). The states labelled m1–m4 are responsible for modelling the interesting motif, while the other states model the non-interesting remainder of the sequence.
Figure 2
Figure 2
A multiple-uncounted SMM containing two motifs. The black dots are silent states, which are not responsible for modelling any part of the sequence.
Figure 3
Figure 3
Likelihoods of a set of test sequences, given mosaic background models of various orders and class numbers.
Figure 4
Figure 4
(a) The original HLF motif from JASPAR. (b) Results for searching for HLF in a set of 150 base sequences using MEME. (c) MEME with 200 base sequences. (d) NestedMICA with 600 base sequences. (e) NestedMICA with 700 base sequences.
Figure 5
Figure 5
A selection of mammalian JASPAR weight matrices that are used for synthetic data tests.
Figure 6
Figure 6
ROC curves for the best matches to the SRE sites in the NestedMICA and MEME results.
Figure 7
Figure 7
The MEF2 motif derived from curated sites, and the corresponding high-scoring motifs from NestedMICA and MEME.
Figure 8
Figure 8
The SRE motif derived from curated sites, and the corresponding high-scoring motifs from NestedMICA and MEME.
See this image and copyright information in PMC

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