2 <- 1,2,3 for number of codons to be analysed; set to 4 if require 3 codon dhfr genotype omitting 'impossible' clones
8 <- level of precision required for ML estimate
3 <- level of precision required for CI estimation
12 <- maximum number of clones in any sample
n <- (must be y or n) whether  'minority' genotypes will be missed in typing
0.3 <-the detection limit if minority genotypes are missed e.g. 0.3 means genotypes present at frequency less than 30% will be missed… 
y <- (must be y or n) whether  MOI is known for each sample
1 <- distribution type to be used if MOI is unknown 
n <- (must be y or n) whether to check hillclimbing always converges on the same ML 'peak'
n <- (must be y or n) whether to check programme accuracy by simulating datasets and checking 95% of estimates fall within the 95% CI
H <- (must be H or L in uppercase) If a dataset is simulated should it be for a High or Low transmission setting?
100 <- required size of dataset for simulations to check programme accuracy
1000 <- number of replicates used to check hillclimbing or programme accuracy
0    <- a redundant parameter, set to zero. [This allows later programme versions to acquire additional information without making previous input files incompatible]
0    <- a redundant parameter, set to zero.
0    <- a redundant parameter, set to zero.
0    <- a redundant parameter, set to zero
0    <- a redundant parameter, set to zero.