1
Introduction
1.1
Preface
1.2
Overview
1.3
Prerequisites
1.4
References
2
Installing a Linux environment & SLiM on the WSL
2.1
Overview
2.2
Why Linux?
2.3
The Windows Subsystem for Linux
2.4
Installing WSL
2.5
Installing a desktop and setting up X11
2.6
Building SLiM
2.7
Installing other useful apps
2.8
Footnotes
3
Terminal Shortcuts and Basics
3.1
Overview
3.2
Navigating folders
3.3
Installing and updating software
3.4
Input and output
3.5
Git
3.5.1
Git Branches and Pull Requests
3.5.2
Git for SLiM
4
Placeholder Chapter
5
Polygenic Adaptation in SLiM
5.1
Overview
5.2
A Single Polygenic Trait (Chp5-1_1T.slim)
5.3
Parameters
5.3.1
Ne
5.3.2
del_mean and del_shape
5.3.3
mutWeights
5.3.4
rwide
5.3.5
genomelength
5.3.6
locimu, locisigma, and locidist
5.3.7
width
5.3.8
printH
5.3.9
samplerate
5.3.10
modelindex
5.4
Footnotes
6
Running SLiM in Parallel
6.1
Overview
6.2
SLiM at the Command Line
6.3
Running SLiM via Bash
6.4
Running SLiM via R
6.5
Running SLiM in Python
6.6
Running SLiM via a C++ Program
6.7
Writing SLiM code with parallelism in mind
6.7.1
Single file output
6.7.2
Multiple file output
6.8
Footnotes
7
Running SLiM on a HPC Cluster
7.1
Overview
7.2
Connecting to Tinaroo and Set-up
7.3
PBS Scripts
7.4
Multi-node jobs
7.4.1
Job array SLiM jobs
7.4.2
Embedded Nimrod SLiM jobs
7.5
Estimating Simulation Time
7.6
Other Considerations
7.7
Footnotes
8
Latin Hypercube Sampling
8.1
Overview
8.2
What is Latin hypercube sampling?
8.3
Generating hypercubes in R
8.4
Running SLiM with hypercube parameters
8.5
Considerations
8.6
App
9
Working with SLiM data
9.1
Overview
9.2
An example of saving space in custom SLiM output
9.3
Compression
9.4
Footnotes
Polygenic SLiMulations: Investigating polygenic adaptation with SLiM 3.
4
Placeholder Chapter
This will be replaced by something else. In the mean time, enjoy this cat picture:
