FITS input

FITS requires two types of input: Data file and Parameters file.

Data file

This file is expected to hold observed allele information from the system under study. FITS expects a tab-delimited textual file, with following columns:

  1. gen for the generation of the observation
  2. allele for the observed state
  3. freq for the measured frequency for that state
  4. position for the position number for which the frequency data is given (optional)


FITS assumes the columns to appear in the above order.


The allele with the highest frequency at the first available time point will be defined as WT (w=1).

Example data file
gen allele freq position
0 0 1 1
0 1 0 1
1 0 1 1
1 1 0 1
2 0 0.99999 1
2 1 1e-05 1
3 0 0.9999899998 1
3 1 1.00002e-05 1
4 0 0.9999899998 1
4 1 1.00002e-05 1
5 0 0.9999600016 1
5 1 3.99984e-05 1

You can also download an example.


For each generation, the sum of frequencies for the different alleles should be 1.


FITS accepts allele frequencies at a given loci. Sequencing techniques tend to vary in their accuracy, so sometimes the provided allele frequencies may be inaccurate. If using inaccurate input, FITS inferences may be inaccurate as well. Specific examples include:

  1. Inference of fitness of highly deleterious mutations where the accuracy threshold of sequencing is worse than the mutation rate.
  2. Inference of mutation rate from neutral alleles when the number of generations X the mutation rate is lower than the accuracy threshold of the sequencing.
  3. Inference of mutation rate or fitness when very shallow sequencing is available (due to limited sampling or limited sequence coverage).

Parameters file

This file provides FITS with population genetics parameters information of the system under study. Each line in this file represents a different parameter to set, where a space exists between the name of the parameter and its value: <parameter_name> <parameter value>.


If you want to put comments within the parameters file, just add # at the beginning of the comments’ lines.

You can also download an example.

General parameters

Parameter name Type Description
N Integer Size of population
sample_size Integer Size of observed population (e.g., sequenced genomes)
bottleneck_size Integer Size of the population transferred on a bottleneck event
bottleneck_interval* Integer Number of generations separating between bottleneck events (default: 0)
num_alleles Integer Number of alleles observed in all loci
mutation_rateX_Y Float Rate of mutation of allele X to allele Y. Not required if mutation rate is to be inferred
fitness_alleleX Float Fitness value assigned to allele X. Not required if fitness is to be inferred
logistic_growth* Float 1: model the population growth throughout the generations with a logistic growth model (default: 0)
logistic_growth_K Float Logistic model - upper bound
logistic_growth_r Float Logistic model - proportionality constant

*parameter value of 0 means disabled/off; positive values mean enabled/on.

ABC parameters

Parameter name Type Description
num_samples_from_prior Integer How many simulations to perform
acceptance_rate Float Fraction of best simulations to utilize for the inference of the parameter.

Single simulation

Parameter name Type Description
num_generations Integer Number of generations to simulate
init_freq_alleleX Float Initial frequency of allele X

Fitness inference parameters

Parameter name Type Description
fitness_prior Text
One of the following:
uniform (for Uniform distribution)
log_normal (based on Bons et al. 2018)
smoothed_composite (default)
See the distribution of the above priors on a (0,2) fitness here
min_fitness_alleleX Float The minimum fitness value (inclusive) that may be assigned to allele X
max_fitness_alleleX Float The maximum fitness value (exclusive) that may be assigned to allele X

Mutation rate inference parameters

X and Y are alleles defined in the data file (i.e., 0 and 1).

Parameter name Type Description
min_log_mutation_rateX_Y Float Minimum (inclusive) n for mutation rate 10^n from alleleX to allele Y
max_log_mutation_rateX_Y Float Maximum (exclusive) n for mutation rate 10^n from alleleX to allele Y

Population size inference parameters

Parameter name Type Description
Nlog_min Float Minimum (inclusive) exponent n for population size 10^n
Nlog_max Float Maximum (exclusive) exponent n for population size 10^n