linzhi2013 / lcwgs-simulation

A beginner’s guide to low-coverage whole genome sequencing for population genomics

Runyang Nicolas Lou, Arne Jacobs, Aryn Wilder, Nina O. Therkildsen

This GitHub repository contains our entire simulation and analysis pipeline. Below are links to markdown files containing the pipeline, and the shell scripts and SLiM scripts used in the pipeline are available in the shell_scripts and slim_scripts folder.

Section 4.1. Population genomic inference for single populations

Simulation workflow with neutral simulation

Data analysis with neutral simulation and the Samtools GL model (including pool-seq comparison)

Data analysis with neutral simulation and the GATK GL model (including pool-seq comparison)

Simulation workflow with neutral simulation, with uneven input across individuals

Data analysis with neutral simulation, with uneven input across individuals (including pool-seq comparison)

Section 4.2. Inference of spatial structure

Simulation workflow with spatially structured populations

Data analysis with spatially structured populations

Simulation workflow with spatially structured populations and lower migration rate

Data analysis with spatially structured populations and lower migration rate

Simulation workflow and data analysis with spatially structured populations and a longer chromosome

Section 4.3. Scans for divergent selection in the face of gene flow

Simulation workflow with divergent selection

Data analysis with divergent selection simulation (including RAD-seq comparison)

Data analysis with divergent selection simulation with a smaller population (including RAD-seq comparison)

Section 5. Application to empirical data

Data acquisition and analysis with Heliconius butterflies

Box 4. Using imputation to bolster genotype estimation from lcWGS

Simulation workflow with neutral simulation used for genotype imputation

Imputation without a reference panel

Miscellaneous

Figures for presentations and the paper