LinearFold.jl

Julia interface to LinearFold RNA structure prediction programs: LinearFold, LinearPartition, LinearSampling, and LinearTurboFold
Author marcom
Popularity
6 Stars
Updated Last
4 Months Ago
Started In
May 2022

Julia interface to LinearFold

Build Status Aqua QA

Unofficial Julia interface to the LinearFold suite of programs for RNA secondary structure prediction. Please cite the applicable original LinearFold, LinearPartition, LinearSampling, or LinearTurboFold publications if you use this library.

The LinearFold, LinearPartition, LinearSampling, and LinearTurboFold programs are supported at the moment. This library calls the binary executables of these programs directly and parses their output.

The name LinearFold derives from the O(n) running time (where n is the sequence length) of calculating an approximate solution, compared to the typical cubic O(n^3) running time for the exact solution. This speedup is achieved by recasting the normal dynamic programming algorithms to work on the sequence left-to-right and by using a beam search approximation. Most algorithms also have a linear or quadratic time dependence on the beam size used. Please refer to the LinearFold publications for further details.

Installation

] add LinearFold

Usage

using LinearFold, Unitful

Keyword argument description

  • model=:vienna: energy model to be used. Valid options are :vienna and :contrafold. Default is :vienna.

  • beamsize=100: size used for beam search approximation. Larger numbers trade longer computation time for more precise answers. Default is 100.

  • constraints: structural constraints of the predicted structure. A string consisting of the characters '?', '.', '(', ')', corresponding to positions that have unspecified base pairing, unpaired, or base-pairing specified by matching parentheses.

  • is_sharpturn=false: enable sharp turns in predictions. Default is false.

  • verbose=false: output extra information from the program runs to stdout. Default is false.

Minimum free energy (MFE) structure of an RNA strand

Uses the LinearFold program to predict the MFE and MFE structure.

# mfe(seq; model, beamsize, constraints, is_sharpturn, verbose)
mfe("GGGAAACCC")  # => (-1.2 kcal mol^-1, "(((...)))")
mfe("GGGAAACCC"; constraints="?(.????)?") # => (0.9 kcal mol^-1, "((.....))")
mfe("GGGAAACCC"; model=:contrafold)  # => (-0.09 kcal mol^-1, ".........")

Base pair probabilities

Uses the LinearPartition program to calculate base pair probabilities.

# bpp(seq; model, beamsize, bpp_cutoff, is_sharpturn, verbose)
bpp("GGGAAACCC") # => (-1.62 kcal mol^-1, sparse(...))
bpp("GGGAAACCC"; bpp_cutoff=0.1)

Pseudoknot structure prediction

Uses the LinearPartition program to predict possibly pseudoknotted secondary structures with a beam search approximation to the ThreshKnot algorithm.

Because the predicted structures can contain pseudoknots, the structure is returned as a list of integers which indicate the base-pairing partner of the current index.

# threshknot(seq; model, beamsize, threshold, is_sharpturn, verbose)
threshknot("GGGAAACCC")  # => (-1.62 kcal mol^-1, [9, 8, 7, 0, 0, 0, 3, 2, 1])
threshknot("GGGAAACCC"; threshold=0.2)

Sample structures from Boltzmann ensemble

Uses the LinearSampling program to return num_samples secondary structures sampled according to their Boltzmann probability for an RNA sequence.

# sample_structures(seq; beamsize, num_samples, is_nonsaving, is_sharpturn, verbose)
sample_structures("GGGAAACCC")  # => [ "((....)).", ... ]
sample_structures("GGGAAACCC"; num_samples=100)

Simultaneous alignment and folding

Uses the LinearTurboFold program to simultaneously align and fold multiple RNA sequences.

# turbofold(sequences; beamsize_hmm, beamsize_cky, iterations,
#                      threshknot_min_helix_len,
#                      threshknot_iterations, threshknot_threshold,
#                      verbose)
turbofold(["GGGAAACCC", "GGCCAAAUGGCCA"])

Maximum expected accuracy (MEA) structure

Uses the LinearPartition program.

# mea(seq; model, beamsize, gamma, is_sharpturn, verbose)
mea("GGGAAACCC")  # => (-1.62 kcal mol^-1, "(((...)))")
mea("GGGAAACCC"; gamma=0.5)  # => (-1.62 kcal mol^-1, ".(.....).")

Zuker suboptimal structures

Uses the LinearFold program.

# zuker_subopt(seq; model, beamsize, delta, is_sharpturn, verbose)
zuker_subopt("GCGCGAAAAAACCCCCCC")  # => [ (2.9 kcal mol^-1, "....(........)...."), ... ]
zuker_subopt("GCGCGAAAAAACCCCCCC"; delta=4.0u"kcal/mol")

Energy of a (sequence, structure) pair

Uses the eval mode of the LinearFold program.

# energy(seq, structure; model, is_sharpturn, verbose)
energy("GGGAAACCC", "(((...)))")  # => -1.2 kcal mol^-1

Partition function only, no base pair probabilities

Uses the LinearPartition program.

# partfn(seq; model, beamsize, is_sharpturn, verbose)
partfn("GGGAAACCC")  # => -1.62 kcal mol^-1

Related Julia packages

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