Dear all,
I was having a look at using flan for estimating mutation rates, from my data. I usually have my data in a dataframe format, and would like to estimate the mutation rate for a number of clones. So my data will look something like
genotype; mutants; final_counts; plating_efficiency
A; 0; 1e9; 1
A; 10; 3e9; 1
A; 5; 2e9; 1
B; 1; 1e9; 0.3
B; 1; 2e9; 0.3
B; 50; 3e9; 0.3
I can easily calculate the mutation rate for each clone with:
library(data.table) as.data.table(data)[, mutestim(mutants,final_counts,method="GF"), by = genotype]
However, as you can see from the mock data, sometimes I will have variation (per genotype) for the plating efficiency. Such that for genotype A, I will have plated the entire culture, but for genotype B, I will have plated just 1/3.
So the problem is when I run:
as.data.table(data)[, mutestim(mutants,final_counts,plateeff=plating_efficiency,method="GF"), by = genotype]
I get the error:
Error in mutestim(res, final, method = "GF", plateff = plating_efficiency) : 'plateff' must be a single positive and <= 1 number. In addition: Warning message: In if (plateff > 1 | length(plateff) > 1) { : the condition has length > 1 and only the first element will be used
So is there a way around this? or would it be possible for a future version of flan to allow plateeff to be chosen from a data frame. I guess this would be useful for a lot of people.
Dear all,
I was having a look at using flan for estimating mutation rates, from my data. I usually have my data in a dataframe format, and would like to estimate the mutation rate for a number of clones. So my data will look something like
genotype; mutants; final_counts; plating_efficiency
A; 0; 1e9; 1
A; 10; 3e9; 1
A; 5; 2e9; 1
B; 1; 1e9; 0.3
B; 1; 2e9; 0.3
B; 50; 3e9; 0.3
I can easily calculate the mutation rate for each clone with:
library(data.table) as.data.table(data)[, mutestim(mutants,final_counts,method="GF"), by = genotype]However, as you can see from the mock data, sometimes I will have variation (per genotype) for the plating efficiency. Such that for genotype A, I will have plated the entire culture, but for genotype B, I will have plated just 1/3.
So the problem is when I run:
as.data.table(data)[, mutestim(mutants,final_counts,plateeff=plating_efficiency,method="GF"), by = genotype]I get the error:
Error in mutestim(res, final, method = "GF", plateff = plating_efficiency) : 'plateff' must be a single positive and <= 1 number. In addition: Warning message: In if (plateff > 1 | length(plateff) > 1) { : the condition has length > 1 and only the first element will be usedSo is there a way around this? or would it be possible for a future version of flan to allow plateeff to be chosen from a data frame. I guess this would be useful for a lot of people.