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© Centre for Modeling & Simulation, Savitribai Phule Pune University
| Title | One size does not fit all: On how Markov model order dictates performance of genomic sequence analyses |
| Author/s |
Leelavati Narlikar
Centre for Modeling and Simulation, Savitribai Phule Pune University, Pune 411 007 India and Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Pune 411 008 Nidhi Mehta Centre for Modeling and Simulation, Savitribai Phule Pune University, Pune 411 007 India Sanjeev Galande National Centre for Cell Science, Savitribai Phule Pune University Campus, Pune 411 007 and Indian Institute of Science Education and Research, Pune 411 021 Mihir Arjunwadkar Centre for Modeling and Simulation, Savitribai Phule Pune University, Pune 411 007 India and National Centre for Radio Astrophysics, Savitribai Phule Pune University Campus, Pune 411 007, India |
| Abstract | The structural simplicity and ability to capture serial correlations make Markov models a popular modeling choice in several genomic analyses, such as identification of motifs, genes and regulatory elements. A critical, yet relatively unexplored, issue is the determination of the order of the Markov model. Most biological applications use a predetermined order for all data sets indiscriminately. Here, we show the vast variation in the performance of such applications with the order. To identify the ‘optimal’ order, we investigated two model selection criteria: Akaike information criterion and Bayesian information criterion (BIC). The BIC optimal order delivers the best performance for mammalian phylogeny reconstruction and motif discovery. Importantly, this order is different from orders typically used by many tools, suggesting that a simple additional step determining this order can significantly improve results. Further, we describe a novel classification approach based on BIC optimal Markov models to predict functionality of tissue-specific promoters. Our classifier discriminates between promoters active across 12 different tissues with remarkable accuracy, yielding 3 times the precision expected by chance. Application to the metagenomics problem of identifying the taxum from a short DNA fragment yields accuracies at least as high as the more complex mainstream methodologies, while retaining conceptual and computational simplicity. |
| Keywords | |
| Download | Journal |
| Citing This Document | Leelavati Narlikar, Nidhi Mehta, Sanjeev Galande, and Mihir Arjunwadkar , One size does not fit all: On how Markov model order dictates performance of genomic sequence analyses . Technical Report CMS-TR-20121224 of the Centre for Modeling and Simulation, Savitribai Phule Pune University, Pune 411007, India (2012); available at http://864230.efsst.group/reports/. |
| Notes, Published Reference, Etc. | Published as Nucleic Acids Research 41(3), 1416-1426 (2012). |
| Contact | mihir AT 864230.efsst.group |
| Supplementary Material |