- Title
- MARS: Motif Assessment and Ranking Suite for transcription factor binding motifs
- Creator
- Kibet, Caleb K
- Creator
- Machanick, Philip
- Date Issued
- 2016
- Date
- 2016
- Type
- article
- Type
- text
- Identifier
- http://hdl.handle.net/10962/61155
- Identifier
- vital:27985
- Identifier
- http://dx.doi.org/10.1101/065615
- Description
- We describe MARS (Motif Assessment and Ranking Suite), a web-based suite of tools used to evaluate and rank PWM-based motifs. The increased number of learned motif models that are spread across databases and in different PWM formats, leading to a choice dilemma among the users, is our motivation. This increase has been driven by the difficulty of modelling transcription factor binding sites and the advance in high-throughput sequencing technologies at a continually reducing cost. Therefore, several experimental techniques have been developed resulting in diverse motif-finding algorithms and databases. We collate a wide variety of available motifs into a benchmark database, including the corresponding experimental ChIP-seq and PBM data obtained from ENCODE and UniPROBE databases, respectively. The implemented tools include: a data-independent consistency-based motif assessment and ranking (CB-MAR), which is based on the idea that `correct motifs' are more similar to each other while incorrect motifs will differ from each other; and a scoring and classification-based algorithms, which rank binding models by their ability to discriminate sequences known to contain binding sites from those without. The CB-MAR and scoring techniques have a 0.86 and 0.73 median rank correlation using ChIP-seq and PBM respectively. Best motifs selected by CB-MAR achieve a mean AUC of 0.75, comparable to those ranked by held out data at 0.76 { this is based on ChIP-seq motif discovery using five algorithms on 110 transcription factors. We have demonstrated the benefit of this web server in motif choice and ranking, as well as in motif.
- Format
- 20 pages
- Format
- Language
- English
- Relation
- bioRxiv
- Relation
- Kibet, C.K. and Machanick, P., 2016. MARS: Motif Assessment and Ranking Suite for transcription factor binding motifs. bioRxiv, p.065615
- Relation
- bioRxiv 1 20 2016
- Rights
- bioRxiv
- Rights
- Use of this resource is governed by the CC-BY-NC-ND 4.0 International license
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