运行几次 pop-gen 模拟，并将每次的结果存储在数据框的新列中

Question

我有一个基本的 Wright-Fisher 模拟，用于两个等位基因，效果非常好，并生成了一个好看的图，显示等位基因按预期固定或偶然消失。它将计算出的每一代都导出到数据框 d 中，因此我手头有每一代的值。我想要做的是运行整个事情说 20 次并自动将每个完整的模拟存储在一个新列中，这样我就可以将它们全部绘制在带有颜色和所有好东西的 ggplot 图表上。我最感兴趣的是获得一个整洁的框架来为项目制作好看的图，而不是惊人的效率。

#Wright Fisher model Mk1

#Simulation Parameters
# n = pop.size
# f = frequency of focal allele
# x = number of focal allele, do not set by hand
# y = number of the other allele, do not set by hand
# g = generations desired
n = 200
f = 0.6
x = (n*f)
y = (n-x)
g = 200

#This creates a data frame of the correct size to store each generation

d = data.frame(f = rep(0,g))

#Creates the graph.
plot(1,0, type = "n", xlim = c(1,200), ylim = c(0,n),
     xlab = "Generation", ylab = "Frequency A")

#Creates the population, this model is limited to only two alleles, and can only plot one
alleles<- c(rep("A",x), rep("a",y))

#this is the loop that actually simulates the population
#It has code for plotting each generation on the graph as a point 
#Exports the number of focal allele A to the data frame
for (i in 1:g){ 
  alleles <- sample(alleles, n, replace = TRUE)
points(i, length(alleles[alleles=="A"]), pch = 19, col= "red")
F = sum(alleles == "A")
d[i, ] = c(F)
}

所以我想运行最后一位多次并以某种方式存储每个完整的迭代。我知道我可以通过嵌套来循环函数，尽管这又快又脏，但这样做只会存储外循环最后一次迭代的值。

Answer 1

这里有很多改进的机会，但这应该会让你继续前进。我只展示了五个模拟，但你应该能够扩展。本质上，将大部分代码放在一个函数中，然后您可以使用 purrr 包中的 map 函数，或者您也可以使用 replicate:

做一些事情

library(tidyverse)

n = 200
f = 0.6
x = (n*f)
y = (n-x)
g = 200

d = data.frame(f = rep(0,g))

run_sim <- function() {
  alleles <- c(rep("A", x), rep("a", y))

  for (i in 1:g) { 
    alleles <- sample(alleles, n, replace = TRUE)
    cnt_A = sum(alleles == "A")
    d[i, ] = c(cnt_A)
  }

  return(d)
}

sims <- paste0("sim_", 1:5)

set.seed(4) # for reproducibility

sims %>%
  map_dfc(~ run_sim()) %>%
  set_names(sims) %>%
  gather(simulation, results) %>%
  group_by(simulation) %>%
  mutate(period = row_number()) %>%
  ggplot(., aes(x = period, y = results, group = simulation, color = simulation)) +
  geom_line()

^{由 reprex package (v0.2.1)}

创建于 2019-03-21

注意：您还可以向 run_sim 函数添加参数，比如 x 和 y（即 run_sim <- function(x, y) { ... }），这样您就可以探索其他可能性。

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运行几次 pop-gen 模拟，并将每次的结果存储在数据框的新列中