mCarts¶
Description¶
mCarts is a hidden Markov model (HMM)-based methods to predict clusters RNA motif sites. Many RBPs recognize very short and degenerate sequences, with targeting specificity achieved by mechanisms such as synergistic binding to multiple clustered sites and modulation of site accessibility through different RNA-secondary structures. mCarts integrates the number and spacing of individual motif sites, their accessibility and conservation, which substantially improves signal to noise ratio. This algorithm learns and quantifies rules of these features, taking advantage of a large number of in vivo RBP binding sites obtained from high throughput sequencing of RNAs isolated by cross-linking and immunoprecipitation (HITS-CLIP). We applied this algorithm to study two representative RBPs, Nova and Mbnl. Despite the very low information content in individual motif elements, our algorithm made very specific predictions for successful experimental validation. Reference data directories specified with the '-lib' argument are located under the ufrc directory also available via the Citation: Zhang, C. †, Lee, K.-Y., Swanson, M.S., Darnell, R.B. † 2013. Prediction of clustered RNA-binding protein motif sites in the mammalian genome. Nucleic Acids Res, in press.
Environment Modules¶
Run module spider mcarts
to find out what environment modules are available for this application.
Environment Variables¶
HPC_MCARTS_REF variable. * HPC_MCARTS_DIR - installation directory * HPC_MCARTS_BIN - executable directory * HPC_MCARTS_REF - reference data directory
Citation¶
If you publish research that uses mcarts you have to cite it as follows:
Zhang, C. †, Lee, K.-Y., Swanson, M.S., Darnell, R.B. † 2013. Prediction of clustered RNA-binding protein motif sites in the mammalian genome. Nucleic Acids Res, in press.
Categories¶
biology, genomics, math