Nothing
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## -----------------------------------------------------------------------------
library(retrocombinator)
## -----------------------------------------------------------------------------
simulateEvolution()
## ---- eval = FALSE------------------------------------------------------------
# # --- NOT RUN (this is an alternative) ---
# recombParams <- RecombParams(recombMean = 1.0)
# activityParams <- ActivityParams(lengthCriticalRegion = 20,
# probInactiveWhenMutated = 0.1)
# simulateEvolution(recombParams = recombParams, activityParams = activityParams)
# # ----------------------------------------
## ---- eval = FALSE------------------------------------------------------------
# # --- NOT RUN (this is an alternative) ---
#
# # Obtain your sequence in your favourite way
# library(Biostrings)
# fastaInput <- readDNAStringSet('path/to/your/FASTA/file')
# yourSequence <- toString(fastaInput$yourSequence)
#
# # Override the sequence parameters and pass it to the simulation
# sequenceParams <- SequenceParams(initialSequence = yourSequence)
# simulateEvolution(sequenceParams = sequenceParams)
# # ----------------------------------------
## -----------------------------------------------------------------------------
data <- parseSimulationOutput('simulationOutput.out')
## ---- eval = FALSE------------------------------------------------------------
# # --- NOT RUN (this is an alternative) ---
#
# # Alternatively, using the pipe operator
# library(magrittr) # For %>%
# data <- simulateEvolution() %>%
# parseSimulationOutput()
#
# # ----------------------------------------
## -----------------------------------------------------------------------------
print(names(data$params))
# Prints out all the parameters the simulation was run with
print(colnames(data$sequences))
# step - timestep in the simulation
# realTime - time since the start of the simulation (in millions of years)
# sequenceId - the unique ID of the sequence (to track it over time); initial
# sequence has sequenceId 0 to (numInitialCopies-1)
# parentMain - the unique ID of the sequence this burst from;
# (-1 if nothing)
# parentOther - the unique ID of the sequence its parent recombined with;
# (-1 if nothing)
# distanceToInitial - the distance to the initial sequence
# isActive - whether or not the sequence is capable of transposition
print(colnames(data$pairwise))
# step - timestep in the simulation
# realTime - time since the start of the simulation (in millions of years)
# sequenceId1 - an ID of a sequence present at the time
# sequenceId2 - an ID of a different sequence present at the time; not all pairs
# are given - that is, for sequences a and b, either (a, b) or (b, a)
# is present as a row but not both
# distancePairwise - the distance between the two sequences
print(colnames(data$familyRepresentatives))
# step - timestep in the simulation
# realTime - time since the start of the simulation (in millions of years)
# familyId - the unique ID of the family representative (to track it over time)
# creationTime - time this family representative was created (in millions of years)
# sequenceId - a sequence belonging to that family (sequences belonging to a
# family are listed as separate rows, and all sequences belonging
# to that family are listed)
print(colnames(data$familyPairwise))
# step - timestep in the simulation
# realTime - time since the start of the simulation (in millions of years)
# familyId1 - an ID of a family representative present at the time
# familyId2 - an ID of a different family representative present at the time;
# not all pairs are given - that is, for sequences a and b, either (a, b) or (b,
# a) is present as a row but not both
# distancePairwise - the distance between the two family representatives
## ---- eval = FALSE------------------------------------------------------------
# summariseEvolution(data) # TODO
## -----------------------------------------------------------------------------
plotEvolution(data, "initial") # Distance to initial sequence
plotEvolution(data, "pairwise") # Pairwise distances between sequences
plotEvolution(data, "families") # Family sizes
## -----------------------------------------------------------------------------
sequenceParams <- SequenceParams(initialSequence = "TCAGTCAGTCAGTCAGTGTG",
numInitialCopies = 10)
activityParams <- ActivityParams(lengthCriticalRegion = 2,
probInactiveWhenMutated = 0.1)
mutationParams <- MutationParams(model = "F81")
burstParams <- BurstParams(burstProbability = 0.2,
burstMean = 2,
maxTotalCopies = 40)
recombParams <- RecombParams(recombMean = 2.0,
recombSimilarity = 0.85)
selectionParams <- SelectionParams(selectionThreshold = 0.25)
familyParams <- FamilyParams(familyCoherence = 0.65,
maxFamilyRepresentatives = 15)
simulationParams <- SimulationParams(numSteps = 35,
timePerStep = 1.5)
outputParams <- OutputParams(outputFilename = 'simulationExampleParameters.out',
outputNumInitialDistance = 5,
outputNumPairwiseDistance = 5,
outputNumFamilyLabels = 5,
outputNumFamilyMatrix = 5,
outputMinSimilarity = 0.1)
seedParams <- SeedParams(toSeed = TRUE, seedForRNG = 1)
simulateEvolution(sequenceParams = sequenceParams,
activityParams = activityParams,
mutationParams = mutationParams,
burstParams = burstParams,
recombParams = recombParams,
selectionParams = selectionParams,
familyParams = familyParams,
simulationParams = simulationParams,
outputParams = outputParams)
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