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ETEcalculator

ETEcalculator is used to estimate the end-to-end distance of a sequence. It generates a stochastic sample for the sequence and then uses polymer physics to estimate the end-to-end distance in nanometers. ETEcalculator-smp is the parallel version built using OpenMP.

USAGE: ETEcalculator <sequence file> [options]

OR

ETEcalculator-smp <sequence file> [options]

Required parameters:

<seq file> The name of a sequence file containing input data.
Note that lowercase nucleotides are forced single-stranded in structure prediction.

Options that do not require added values:

-h, -H, --help Display the usage details message.
-r, --raw Output just the mean end-to-end distamce in nanometers. The default is to make output that is more verbose.
-v -V --version Display version and copyright information for this interface.

Options that require added values:

-a, -A, --alphabet Specify the name of a folding alphabet and associated nearest neighbor parameters. The alphabet is the prefix for the thermodynamic parameter files, e.g. "rna" for RNA parameters or "dna" for DNA parameters or a custom extended/modified alphabet. The thermodynamic parameters need to reside in the at the location indicated by environment variable DATAPATH.
The default is "rna" (i.e. use RNA parameters). This option overrides the --DNA flag.
-c -C --constraint Specify a folding constraints file to be applied.
-f, --file Specify a filename to which the results will be written. The default is to write the output to STDOUT.
-n, --number Specify the size of the stochastic sample. The default is to use 1000 structures.
-s, -S, --seed Specify the random number seed. The default seed is 1234.

Notes for smp:

ETEcalculator-smp, by default, will use all available compute cores for processing. The number of cores used can be controlled by setting the OMP_NUM_THREADS environment variable.

 

References:

  1. Lai, W.C., Kayedkhordeh, M., Cornell, E.V., Farah, E., Bellaousov, S., Rietmeijer, R., Mathews, D.H., and Ermolenko, D.N.
    "mRNAs and lncRNAs intrinsically form secondary structures with short end-to-end distances."
    Nature Communications. 9: 4328.(2018).
  2. Aalberts, D.P.and Nandagopa, N.
    "A two length scale polymer theory for RNA loop free energies and helix stacking."
    RNA, 16: 1350–1355 (2010).
  3. Reuter, J.S. and Mathews, D.H.
    "RNAstructure: software for RNA secondary structure prediction and analysis."
    BMC Bioinformatics, 11:129. (2010).