Encode "License-Plates" from Sequences and Decode Them Back
It can be used to create/encode molecular "license-plates" from sequences and to also decode the "license-plates" back to sequences.  While initially created for transfer RNA-derived small fragments, this tool can be used for any genomic sequences including but not limited to: transfer RNA-derived small fragments, microRNAs, etc. The detailed information can reference to the Pliatsika V, Loher P, Telonis AG, Rigoutsos I (2016) <doi:10.1093/bioinformatics/btw194>.

It can be used to create/encode molecular "license-plates" from sequences and to also decode the "license-plates" back to sequences.  While initially created for transfer RNA-derived small fragments (tRFs), this tool can be used for any genomic sequences including but not limited to: tRFs, microRNAs, etc. The detailed information can reference to Pliatsika V, Loher P, Telonis AG, Rigoutsos I (2016) <doi:10.1093/bioinformatics/btw194>. It can also be used to annotate tRFs. The detailed information can reference to Loher P, Telonis AG, Rigoutsos I (2017) <doi:10.1038/srep41184>.

Mutant Identification through Phenotypic High throughput Enabled
NOrmalization
Shannon M. Bell <bell.shannonm@gmail.com>,  Lyle D. Burgoon <burgoon.lyle@epa.gov>
This package contains functions to carry out processing of high throughput data analysis and detection of putative hits/mutants.
Contents include a function for post-hoc quality control for removal of outlier sample sets, a median-based normalization method for use in
datasets where there are no explicit controls and where most of the responses are of the wildtype/no response class (see accompanying paper).
The package also includes a way to prioritize individuals of interest using am empirical cumulative distribution function. Methods for
generating synthetic data as well as data from the Chloroplast 2010 project are included.

Mutant Identification through Probabilistic High throughput
Enabled NOrmalization
Shannon M. Bell <bell.shannonm@gmail.com>, Lyle D. Burgoon
<burgoon.lyle@epa.gov>
This package contains functions to carry out processing of
high throughput data analysis and detection of putative
hits/mutants.  Contents include a function for post-hoc quality
control for removal of outlier sample sets, a median-based
normalization method for use in datasets where there are no
explicit controls and where most of the responses are of the
wildtype/no response class (see accompanying paper).  The
package also includes a way to prioritize individuals of
interest using am empirical cumulative distribution function.
Methods for generating synthetic data as well as data from the
Chloroplast 2010 project are included.