Nothing
## ----prepare-data, eval=FALSE-------------------------------------------------
# library(dowser)
# library(dplyr)
# library(ggtree)
#
# # load example AIRR tsv data
# data(ExampleAirrTyCHE)
#
# # set up time/date trait
# ExampleAirrTyCHE$sample_time <- as.numeric(ExampleAirrTyCHE$sample_time)
#
# # trait value of interest
# trait="location"
#
# clones <- formatClones(
# ExampleAirrTyCHE,
# traits = c(trait, "sample_time"),
# germ = "germline_alignment"
# )
#
# # Column shows which location the B cell was obtained from
# print(table(ExampleAirrTyCHE[[trait]]))
## ----print-table, echo=FALSE, warning=FALSE, message=FALSE--------------------
library(dowser)
data(ExampleAirrTyCHE)
trait="location"
print(table(ExampleAirrTyCHE[[trait]]))
## ----estimate-gc-clock-rate, eval=FALSE---------------------------------------
# gc_cells = filter(ExampleAirrTyCHE, location=="germinal_center")
# gcf = formatClones(gc_cells, traits=c("location","sample_time"),
# germ="germline_alignment")
#
#
# gctrees = getTrees(gcf, build="pml", sub_model="HKY")
#
# plotTrees(gctrees)[[1]] + geom_tippoint(aes(color=sample_time))
## ----eval=FALSE---------------------------------------------------------------
# # edit to your BEAST installation path
# beast <- "/Applications/BEAST 2.7.7/bin/"
#
# # estimate clock rate of GC B cells
# # if you don't care about convergence, reduce mcmc_length
# # ensure you are providing the correct path to the template file downloaded earlier (see Requirements)
# gctree = getTimeTreesIterate(gcf,
# beast=beast,
# template="StrictClock_Standard_EmpFreq.xml",
# dir="temp",
# id="gc_strict",
# time="sample_time",
# mcmc_length=1e6,
# iterations=10,
# nproc=2,
# CLOCK_RATE_INIT=0.001,
# KAPPA_PRIOR_M=0.67,
# KAPPA_PRIOR_S=0.2,
# ignore=c("freqParameter"))
#
#
# gcrate_tree = mean(sapply(gctree$parameters, function(x)filter(x,item=="geneticClockRate")$mean))
# print(gcrate_tree)
## ----echo=FALSE---------------------------------------------------------------
print(0.000363)
## ----eval=FALSE---------------------------------------------------------------
# gcrate_slope = mean(correlationTest(gctrees, time="sample_time")$slope)
# print(gcrate_slope)
## ----echo=FALSE---------------------------------------------------------------
print(0.0003686277)
## ----eval=FALSE---------------------------------------------------------------
# mixed_trees <- getTimeTreesIterate(
# clones,
# beast = beast,
# template = "TraitLinkedExpectedOccupancy_EstTraitClockRates_EmpFreq.xml",
# trait = trait,
# time = "sample_time",
# dir = "temp",
# id = "tyche_eo_est",
# log_every = "auto",
# nproc = 2,
# KAPPA_PRIOR_M = 0.67,
# KAPPA_PRIOR_S = 0.2,
# TRAIT_RATE_MEAN_1 = gcrate_tree,
# TRAIT_RATE_MEAN_2 = 0.000001,
# TRAIT_RATE_SIGMA_1 = gcrate_tree * 0.01,
# TRAIT_RATE_SIGMA_2 = 0.001,
# RATE_INDICATORS = "1 0",
# TRANSITION_RATE_ALPHA_1 = 0.1,
# TRANSITION_RATE_ALPHA_2 = 1.0,
# TRANSITION_RATE_BETA_1 = 0.1,
# TRANSITION_RATE_BETA_2 = 1.0,
# log_target = 2000,
# mcmc_length = 1e6,
# ignore = c("freqParameter"),
# iterations = 20
# )
## ----plot-mixed-trees-result, eval=FALSE--------------------------------------
# plotTrees(mixed_trees, scale=10)[[1]] + geom_point(aes(fill=location), pch=21, size=3)
## ----tree-height-parameter, eval=FALSE----------------------------------------
# print(mixed_trees$parameters[[2]] %>% filter(item=="TreeHeight"))
## ----echo=FALSE---------------------------------------------------------------
tree_height_param <- " item mean stderr stddev median X95.HPDlo X95.HPDup ACT ESS geometric.mean
1 TreeHeight 236.0621 1.595335 19.36631 234.2536 201.9269 275.1676 122150.1 147.3636 235.2881"
cat(tree_height_param)
## ----logged-parameters, eval=FALSE--------------------------------------------
# print(mixed_trees$parameters[[2]]$item)
## ----echo=FALSE---------------------------------------------------------------
logged_items <- c("posterior", "likelihood","prior",
"treeLikelihood.tyche_eo_est_2", "TreeHeight",
"rateIndicator.type.1", "rateIndicator.type.2",
"relativeGeoRates.type.1", "relativeGeoRates.type.2",
"typeSwitchClockRate", "kappa.tyche_eo_est_2",
"BayesianSkyline", "bPopSizes.1", "bPopSizes.2", "bPopSizes.3",
"bPopSizes.4", "bPopSizes.5", "bGroupSizes.1",
"bGroupSizes.2", "bGroupSizes.3", "bGroupSizes.4",
"bGroupSizes.5", "freqParameter.tyche_eo_est_2.1",
"freqParameter.tyche_eo_est_2.2",
"freqParameter.tyche_eo_est_2.3",
"freqParameter.tyche_eo_est_2.4", "traitfrequencies.type.1",
"traitfrequencies.type.2", "typeLinkedRates.1", "typeLinkedRates.2")
print(logged_items)
## ----read-beast-output, eval=FALSE--------------------------------------------
# mixed_trees <- readBEAST(clones, dir="temp", id="tyche_eo_est", beast=beast, trait=trait)
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