Package: drtransformer
DrTransformer -- heuristic cotranscriptional folding.DrTransformer (short for "DNA-to-RNA transformer") is a program for heuristic
and deterministic cotranscriptional folding simulations of RNA molecules. The
code of this project is available under MIT license, however this software
depends on theViennaRNApackage which is available through theViennaRNA
license.InstallationIf you already have the Python bindings of theViennaRNApackage installed,
then the latest stable release of DrTransformer can be installed from PyPI:~$pipinstalldrtransformerDrTransformer can also be installed with bioconda to resolve theViennaRNAdependency automatically. First, make surebiocondais set up properly with:~$condaconfig--addchannelsdefaults~$condaconfig--addchannelsbioconda~$condaconfig--addchannelsconda-forge~$condaconfig--setchannel_prioritystrictSecond, install or update your DrTransformer installation.~$condainstalldrtransformerTesting/ContributingTo install the latest development version of DrTransformer, clone the
repository and run:~$pipinstall.[dev]Use the following command to run all present unittests:~$python-mpytestPlease provide unittests if you are submitting a pull request with a new feature.UsageUntil further documentation is available, please use the--helpoptions of the
command line executables:~$DrTransformer--help~$DrPlotter--helpAn example cotranscriptional folding simulationWe show simulations of three sequences designed byXayaphoummine et
al. (2006).  Briefly, two sequences are composed of the same palindromic
subsequences (A, B, C, D) in forward and reverse order (ABCDandDCBA); the
third sequence (DCMA) has a point mutation which changes B to M. The
experiment demonstrates how the order of helix formation determines which
structures are formed at the end of transcription, an effect that cannot be
observed with a thermodynamic equilibrium prediction, because the free energies
of, for example, the helices A:B and B:A are almost the same due to their
palindromic subsequences.  The three input filesABCD.fa,DCBA.faandDCMA.facontain a fasta header and the respective sequence from the
original publication.  Those files can be found in the subfolderexamples/.~$catABCD.fa|DrTransformer--nameABCD--o-prune0.01--logfileThis command line call of DrTransformer produces two files:ABCD.logcontains a human-readable summary of the cotranscriptional folding process.ABCD.drfcontains the details of the cotranscriptional folding simulation in theDrFornafile format.Structure-based data analysisDrPlotter supports different types of visual analysis for the.drffile
format. The following command line call reads the previously generated fileABCD.drfand produces a plot calledABCD.png.~$catABCD.drf|DrPlotter--nameABCD--formatpngThe legend ofABCD.pngmust be interpreted in combination with theABCD.logfile.Note that the structure IDs from your newly generated files might not
match the ones shown here.For example, to see which structures are shown at
the simulation of nucleotide 73, read the log file entries for this transcript
length:73    1 .(..(((((((((((((((....)))))))))))))))..).(((((((((.......)))))))))...... -42.60 +[0.0213 -> 0.9876] ID = 24
73    2 ....(((((((((((((((....))))))))))))))).(..(((((((((....)).)))))))..)..... -39.90 -[0.9787 -> 0.0124] ID = 25The logfile lists two structures (in order of their free energy), it shows
their occupancy at the start of the simulation and at the end of a simulation
in square brackets, and it provides the ID to follow a specific structure
through the transcription process (+/- indicate a change in occpancy). The IDs
are used as labels in the plotABCD.png.Motif-based data analysisInstead of following specific structures, it is often more helpful to visualize
when specific helical motifs are formed in the ensemble. Generally, we refer to
a helix formed from sequences A and B as A:B, etc. All potential helices
plotted here are provided in dot-bracket notation in the filesABCD.motifs,DCBA.motifsandDCMA.motifs.~$catABCD.drf|DrPlotter--nameABCD-motifs--moleculeABCD--formatpng--motiffileABCD.motifs--motifsA:BC:DA:DB:C~$catDCBA.drf|DrPlotter--nameDCBA-motifs--moleculeDCBA--formatpng--motiffileDCBA.motifs--motifsB:AD:CD:AC:B~$catDCMA.drf|DrPlotter--nameDCMA-motifs--moleculeDCMA--formatpng--motiffileDCMA.motifs--motifsM:AD:CD:AC:MABCD forms only structures A:B and C:D but not A:D and B:C. Also, helix C:D is
not formed "immediately", because there is a competing structure which
is cotranscriptionally favored (see ID 25 from the previous anlysis).DCBA forms structures with all motifs. The helical structures C:B and
D:A dominate with more than 90%, the helices D:C and B:A are
below 10% of the population. Eventually, D:C and B:A will be
dominant, but not on the time scale simulated here. (Can you repeat the analysis
to see how much time it needs until D:C and B:A dominate the ensemble?)As shown in the publication, a single point mutation (from DCBA to DCMA) is
sufficient to drastically shift occupancy of helices: M:A and D:C
are more occupied at the end of transcription than D:A and C:M.Tips and tricksThe header of the logfile contains all relevant DrTransformer parameters that generated the file.You can use the parameter--plot-minhto group similar structures (separated by energy barriers < plot-minh) together.
In contrast to the--t-fastparameter, this will not affect the accuracy of the model.Use--pause-sitesto see the effects of pausing at specific nucleotides on cotranscriptional folding.Motifs for DrPlotter can also contain 'x' in the dot-bracket notation formust be unpaired.Versionv0.12 -- perparing for official releasechanged --t-lin, --t-log defaults and fixed --t-lin=1, --t-log=1fixed potential issues with --t-end = --t-extadapted README example to publicationv0.11 -- using lonely base-pairsremoved the --noLP default (added parameter setting)added profiling option for runtime optimizationusing --cg-auto default paramterusing k0=1e5, t-ext=0.04 default parameteradded new visulization types and fixed motif file inputadded epsilon to t-fast sanity checkv0.10 -- moved to beta status (first official release)changes in parameter defaultsbugfix in linalgnew DrPlotter simulation layout and motif plottingrepaired code to enable plotting including pause sitesv0.9 -- standalone package (no official release)extraction from the [ribolands] package to a standalone Python package.using scipy and numpy for matrix exponentials (instead of [treekin])implemented lookahead to skip pruning of potentially relevant future structuresCiteStefan Badelt, Ronny Lorenz, Ivo L Hofacker:DrTransformer: heuristic
cotranscriptional RNA folding using the nearest neighbor energy model,
Bioinformatics, Volume 39, Issue 1, January 2023,https://doi.org/10.1093/bioinformatics/btad034