Tutorial-3.md

@@ -2,10 +2,9 @@
 
 We sometimes have multiple demes, i.e. different types of individuals that contribute to the phylogeny or that can be sampled (e.g. juveniles vs. adults or acute vs. chronic infections).
 
-We illustrate this example using a birth-death (BD) model with two patches (labeled 1 and 2) and migration between these patches (at a rate *μ*).
+We illustrate this example using a birth-death (BD) model with two patches (labeled 1 and 2) and migration between these patches (at a rate _μ_).
 
-Initializing the system
------------------------
+## Initializing the system
 
 ```math
 \begin{aligned}
@@ -49,7 +48,7 @@ the parameters values are
 theta <- list(gamma1 = c(0.2, 0.09), gamma2 = 0.1, mu1 = 0.025, mu2 = 0.021, beta1 = c(0.26,0.37), beta2 = 0.414)
 ```
 
-and the time step (for the *τ*-leap and mixed algorithms) is:
+and the time step (for the _τ_-leap and mixed algorithms) is:
 
 ```r
 dT <- 0.01
@@ -61,8 +60,7 @@ A safe version of the simulator `bd_simu()` is:
 safe_bd_simu <- function(...) safe_run(bd_simu, ...)
 ```
 
-Tau-leap trajectory simulation
-------------------------------
+## Tau-leap trajectory simulation
 
 We perform the simulations using:
 
@@ -93,10 +91,10 @@ Graphically, we get:
 ```r
 plot(trajbd_tl)
 ```
-<img src="uploads/3a2faeb23a8cbd99b5e83742bf5cebeb/unnamed-chunk-37-1.png"  width="350" height="230">
 
-Phylogeny simulation
---------------------
+![](uploads/3a2faeb23a8cbd99b5e83742bf5cebeb/unnamed-chunk-37-1.png){width="350" height="230"}
+
+## Phylogeny simulation
 
 ### With known sampling dates and known proportion of sampling
 
@@ -139,7 +137,49 @@ ape::plot.phylo(bd_tree, root.edge = T, no.margin = F, align.tip.label = T)
 nodelabels(pch=20,col=inode_cols)
 ```
 
-<img src="uploads/277ee24ec0551ae8e833147256790e0e/unnamed-chunk-41-1.png"  width="350" height="400">
+![](uploads/277ee24ec0551ae8e833147256790e0e/unnamed-chunk-41-1.png){width="350" height="400"}
+
+### With known sampling dates, each assigned to a compartment by the user
+
+One can give as input, sampling dates assigned to a compartment, in which case the option `sampled` is not required.
+
+```r
+dates_bd <- seq(from=2015, to=2018, length.out=100)
+dates_bd <- data.frame(Date=sample(dates_bd),Comp=c(rep("I1",20),rep("I2",80)))
+head(dates_bd)
+#>       Date Comp
+#> 1 2017.212   I1
+#> 2 2015.515   I1
+#> 3 2017.606   I1
+#> 4 2015.576   I1
+#> 5 2017.515   I1
+#> 6 2015.030   I1
+```
+
+Now let's simulate a phylogeny with sampling dates assigned to a compartment by the user.
+
+```r
+bd_tree <- simulate_tree(
+  simuResults = trajbd_tl,
+  dates = dates_bd,
+  deme = c("I1", "I2"),
+  root = "I2", # type of individual at the root of the tree
+  nTrials = 3,
+  addInfos = TRUE) # additional info for each node
+```
+
+We can plot the phylogeny and color the external nodes given the compartment.
+
+```r
+tips_cols <- ifelse(grepl(x=bd_tree$tip.label,pattern="I2"),"blue","red")
+```
+
+```r
+ape::plot.phylo(bd_tree, root.edge = T, no.margin = F, show.tip.label = F)
+tiplabels(pch=20,col=tips_cols)
+```
+
+![](uploads/93146df8aff6c245d2aa599f5441d7ed/unnamed-chunk-45-1.png){width="350" height="400"}
 
 ### With known sampling dates, each assigned to a compartment by the user
 
@@ -181,4 +221,51 @@ ape::plot.phylo(bd_tree, root.edge = T, no.margin = F, show.tip.label = F)
 tiplabels(pch=20,col=tips_cols)
 ```
 
-<img src="uploads/93146df8aff6c245d2aa599f5441d7ed/unnamed-chunk-45-1.png"  width="350" height="400">
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+![unnamed-chunk-39-1](uploads/76b95fce52ff904179896995877e1ff5/unnamed-chunk-39-1.png){width="350" height="400"}
+
+### With only known sampling dates
+
+In the case where the user has no information on the sampling proportions or the assignment of sampling dates on any compartment, the algorithm will randomly assign each sampling date to a compartment. The user gives as input sampling dates:
+
+```r
+dates_bd <- seq(from=2015, to=2018, length.out=100)
+```
+
+Now let's simulate a phylogeny with sampling dates and no information about the sampling schemes :
+
+```r
+bd_tree <- simulate_tree(
+  simuResults = trajbd_tl,
+  dates = dates_bd,
+  sampled = c("I1","I2"),
+  deme = c("I1", "I2"),
+  root = "I2", # type of individual at the root of the tree
+  nTrials = 10,
+  addInfos = TRUE) # additional info for each node
+```
+
+```r
+ape::plot.phylo(bd_tree, root.edge = T, no.margin = F, show.tip.label = F)
+```
+
+![unnamed-chunk-42-1](uploads/8e810a1aee94cc83e2958906528d2303/unnamed-chunk-42-1.png){width="350" height="400"}
+
+### Without given sampling dates
+
+Let's simuate a phylogeny where simulated deaths in the trajectory generate leaves. This can be done with the `isFullTrajectory` option.
+
+```r
+bd_tree <- simulate_tree(
+  simuResults = trajbd_tl,
+  deme = c("I1", "I2"),
+  root = "I2", # type of individual at the root of the tree
+  nTrials = 10,
+  isFullTrajectory = TRUE, # deads generate leaves
+  addInfos = TRUE) # additional info for each node
+```
+
+```r
+ape::plot.phylo(bd_tree, root.edge = T, no.margin = F, show.tip.label = F)
+```
+
+![unnamed-chunk-44-1](uploads/96af71df9f69292d7f9272aa713090ab/unnamed-chunk-44-1.png){width="350" height="400"}
\ No newline at end of file