mutation comparison

mutation comparison

normal <- read.csv('Downloads/normal_mr_mutations.csv')
r10 <- read.csv('Downloads/mr_10_mutations.csv')
r100 <- read.csv('Downloads/mr_100_mutations.csv')

nrow(normal)

## [1] 24542

summary(normal$mutation_rate)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   0.005   0.005   0.040   0.111   0.180   0.500

barplot(table(normal$mutation_rate))

nrow(r10)

## [1] 5713

summary(r10$mutation_rate)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.0050  0.0100  0.0450  0.1154  0.1850  0.5000

barplot(table(r10$mutation_rate))

nrow(r100)

## [1] 595

summary(r100$mutation_rate)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.0050  0.0100  0.0500  0.1260  0.2075  0.5000

barplot(table(r100$mutation_rate))

general evals

general_evals <- read.csv('Downloads/gen999_normal_mr.csv')
r10_evals <- read.csv('Downloads/gen999_mr_10.csv')
r100_evals <-read.csv('Downloads/gen999_mr_100.csv')

hist(general_evals$fitness)

hist(r10_evals$fitness)

hist(r100_evals$fitness)

evaluations with reduced mutation rate for strong sites (sign + exponent bits)

mm10 <- read.csv('Downloads/mm_10_mutations.csv')
mm100 <- read.csv('Downloads/mm_100_mutations.csv')

mm10_evals <- read.csv('Downloads/gen1960_mm_10.csv')
mm100_evals <- read.csv('Downloads/gen1820_mm_100.csv')

with strong site mutation rate reduced by factor of 10 (1960 generations):

nrow(mm10)

## [1] 15173

summary(mm10$mutation_rate)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
## 0.00500 0.00500 0.03000 0.09443 0.13500 0.50000

barplot(table(mm10$mutation_rate))

hist(mm10_evals$fitness)

with strong site mutation rate reduced by factor of 100 (1820 generations):

nrow(mm100)

## [1] 10016

summary(mm100$mutation_rate)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.0050  0.0050  0.0300  0.1014  0.1600  0.5000

barplot(table(mm100$mutation_rate))

hist(mm100_evals$fitness)

evaluations with smaller parameter size

ast <- read.csv('Downloads/ast_mutations.csv')
ast_big <- read.csv('Downloads/ast_big_mutations.csv')

ast_evals <- read.csv('Downloads/gen3120_ast.csv')
ast_big_evals <- read.csv('Downloads/gen860_ast_big.csv')

population size of 100 (3120 generations)

nrow(ast)

## [1] 1661

summary(ast$mutation_rate)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##  0.0050  0.0100  0.0450  0.1137  0.1750  0.5000

barplot(table(ast$mutation_rate))

hist(ast_evals$fitness)

population size of 1000 (860 generations)

nrow(ast_big)

## [1] 1901

summary(ast_big$mutation_rate)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
## 0.00050 0.00150 0.00600 0.03695 0.03100 0.49100

barplot(table(ast_big$mutation_rate))

hist(ast_big_evals$fitness)