Simulated Identity by Descent Data for DISC Analysis

IBD_simulation_data

Format

A dataframe with 45 rows and 6 columns representing pairwise genetic and geographic distances:

smpl1, smpl2: Integer sample identifiers (1-10)
deme1, deme2: Factor deme (location) identifiers (1-3)
gendist: Numeric genetic distances in (0,1) based on simulated identity by descent
geodist: Numeric geographic distances (500, 1000) representing spatial separation

Source

Simulated toy dataset for testing and demonstration purposes. Generated using an exponential decay relationship between genetic relatedness and geographic distance. Not intended for real-world analysis - use for testing DISC functions and understanding expected input format.

Details

This dataset contains pairwise comparisons between samples from 3 demes:

Deme 1-2 pairs: Geographic distance = 500
Deme 1-3 pairs: Geographic distance = 1000
Deme 2-3 pairs: Geographic distance = 1500

The data follows an isolation-by-distance model where genetic similarity decreases exponentially with geographic distance, modulated by deme-specific inbreeding coefficients.

Examples

# Load the dataset
data("IBD_simulation_data")

# View structure
str(IBD_simulation_data)
#> tibble [33 × 6] (S3: tbl_df/tbl/data.frame)
#>  $ smpl1  : int [1:33] 1 1 1 1 1 1 1 2 2 2 ...
#>  $ smpl2  : int [1:33] 4 5 6 7 8 9 10 4 5 6 ...
#>  $ deme1  : Factor w/ 3 levels "1","2","3": 1 1 1 1 1 1 1 1 1 1 ...
#>  $ deme2  : Factor w/ 3 levels "1","2","3": 2 2 2 3 3 3 3 2 2 2 ...
#>  $ gendist: num [1:33] 0.121 0.645 0.402 0.209 0.312 ...
#>  $ geodist: num [1:33] 500 500 500 1000 1000 1000 1000 500 500 500 ...

# Basic usage with disc function
if (FALSE) { # \dontrun{
start_params <- c("1" = 0.2, "2" = 0.3, "3" = 0.4, "m" = 800)
result <- disc(IBD_simulation_data, start_params, steps = 100)
} # }