Merge pull request #3 from Tuks-ICMM/PCA-and-Fixation

Pca and fixation

.github/workflows/jekyll-gh-pages.yml

@@ -1,5 +1,5 @@
 # Sample workflow for building and deploying a Jekyll site to GitHub Pages
-name: Deploy Jekyll with GitHub Pages dependencies preinstalled
+name: Deploy Jekyll Docs site
 
 on:
   # Runs on pushes targeting the default branch

docs/00-index.md

@@ -10,7 +10,7 @@ nav_order: 1
 
 <!-- START - Links, Badges and Markdown Variables -->
 <div>
-    <img src="https://github.com/Tuks-ICMM/Pharmacogenetic-Analysis-Pipeline/actions/workflows/snakemake-tests.yml/badge.svg"
+    <img src="https://github.com/Tuks-ICMM/Population-Structure-Workflow/actions/workflows/snakemake-tests.yml/badge.svg"
         alt="Build status badge" />
 </div>
 <div>

docs/03-reference-material/01-quickstart.md

@@ -29,22 +29,22 @@ quickstart
 1. First you will need to download a copy of the pipeline to a location where you can configure and execute it. Navigate to our GitHub repository and retrieve the latest tag information.
 2. Next, you can use `GIT` to clone a copy of the pipeline to your working environment:
     ```bash
-    git clone https://github.com/Tuks-ICMM/Pharmacogenetic-Analysis-Pipeline/releases/tag/{{TAG_VERSION_HERE}} .
+    git clone https://github.com/Tuks-ICMM/Population-Structure-Workflow/releases/tag/{{TAG_VERSION_HERE}} .
     ```
 
     {: .normal }
-    > Tags are available on our GitHub repository under the [releases](https://github.com/Tuks-ICMM/Pharmacogenetic-Analysis-Pipeline/releases) page.
+    > Tags are available on our GitHub repository under the [releases](https://github.com/Tuks-ICMM/Population-Structure-Workflow/releases) page.
 
 ## Prepare data and Metadata
 1. In order to execute the _{{ site.title }}_, you will need to configure the pipeline as well as provide information about the analysis you wish to perform. This involves the following configuration files:
-    - `config/config.json` ([General configuration](https://tuks-icmm.github.io/Pharmacogenetic-Analysis-Pipeline/overview/configuration#setting-global-configuration))
-    - `input/datasets.csv` ([Dataset declarations](https://tuks-icmm.github.io/Pharmacogenetic-Analysis-Pipeline/overview/data-requirements#datasets--dataset-files))
-    - `input/samples.csv` ([Sample metadata](https://tuks-icmm.github.io/Pharmacogenetic-Analysis-Pipeline/overview/data-requirements#samples))
-    - `input/locations.csv` ([Genomic location metadata](https://tuks-icmm.github.io/Pharmacogenetic-Analysis-Pipeline/overview/data-requirements#genomic-locations))
-    - `input/transcripts.csv` ([Transcript selection](https://tuks-icmm.github.io/Pharmacogenetic-Analysis-Pipeline/overview/data-requirements#samples))
+    - `config/config.json` ([General configuration](https://tuks-icmm.github.io/Population-Structure-Workflow/overview/configuration#setting-global-configuration))
+    - `input/datasets.csv` ([Dataset declarations](https://tuks-icmm.github.io/Population-Structure-Workflow/overview/data-requirements#datasets--dataset-files))
+    - `input/samples.csv` ([Sample metadata](https://tuks-icmm.github.io/Population-Structure-Workflow/overview/data-requirements#samples))
+    - `input/locations.csv` ([Genomic location metadata](https://tuks-icmm.github.io/Population-Structure-Workflow/overview/data-requirements#genomic-locations))
+    - `input/transcripts.csv` ([Transcript selection](https://tuks-icmm.github.io/Population-Structure-Workflow/overview/data-requirements#samples))
 2. Following configuration, you will need to provide the input data files themselves.
-    - `.vcf.gz` files can be compressed but must be accompanied by a tabix index file ([Discussion here](https://tuks-icmm.github.io/Pharmacogenetic-Analysis-Pipeline/overview/data-requirements#compression-and-indexing))
-    - `.fasta.gz` files for reference sequences must be accompanied by a sequence dictionary file (`.dict`), a fasta index file (`.fa.gz.fai` or `fasta.gz.fai`) and a BGZIP-index (`.fa.gz.gzi`) ([Discussion here](https://tuks-icmm.github.io/Pharmacogenetic-Analysis-Pipeline/overview/configuration#reference-genomes)).
+    - `.vcf.gz` files can be compressed but must be accompanied by a tabix index file ([Discussion here](https://tuks-icmm.github.io/Population-Structure-Workflow/overview/data-requirements#compression-and-indexing))
+    - `.fasta.gz` files for reference sequences must be accompanied by a sequence dictionary file (`.dict`), a fasta index file (`.fa.gz.fai` or `fasta.gz.fai`) and a BGZIP-index (`.fa.gz.gzi`) ([Discussion here](https://tuks-icmm.github.io/Population-Structure-Workflow/overview/configuration#reference-genomes)).
 
 ## Execute analysis
 1. To execute the analysis, we need to compile our metadata and auto-generate a suitable queue-able script for the batch scheduler. To do this, you can use the `run.py` script which generates and queues a hidden generated script `.run.sh` written for your environment. For example:

docs/03-reference-material/04-roadmap.md

@@ -27,7 +27,7 @@ Changelog
 ---
 
 # Roadmap
-See our [Issues tracker](https://github.com/Tuks-ICMM/Pharmacogenetic-Analysis-Pipeline/issues) on GitHub for a list of proposed features (and known issues).
+See our [Issues tracker](https://github.com/Tuks-ICMM/Population-Structure-Workflow/issues) on GitHub for a list of proposed features (and known issues).
 
 <dl>
     <dt>Q1-Q2 2023</dt>

docs/_includes/head_custom.html

@@ -3,7 +3,7 @@
     content="A Snakemake powered pipeline developed to perform variant-effect-prediction, frequency analysis and Admixture analysis given multiple Variant Call Format datasets. This has been developed in partia...">
 
 <!-- OpenGraph Meta Tags -->
-<meta property="og:url" content="https://tuks-icmm.github.io/Pharmacogenetic-Analysis-Pipeline/">
+<meta property="og:url" content="https://tuks-icmm.github.io/Population-Structure-Workflow/">
 <meta property="og:type" content="website">
 <meta property="og:title"
     content="GitHub - Tuks-ICMM/Pharmacogenetic-Analysis-Pipeline: A Snakemake powered pipeline developed to perform variant-effect-prediction, frequency analysis and Admixture analysis given multiple Variant Call Format datasets. This has been developed in partial fulfilment of a MSc in Bioinformatics at the University of Pretoria by Graeme Ford.">
@@ -15,7 +15,7 @@
 <!-- Twitter Meta Tags -->
 <meta name="twitter:card" content="summary_large_image">
 <meta property="twitter:domain" content="github.com">
-<meta property="twitter:url" content="https://tuks-icmm.github.io/Pharmacogenetic-Analysis-Pipeline/">
+<meta property="twitter:url" content="https://tuks-icmm.github.io/Population-Structure-Workflow/">
 <meta name="twitter:title"
     content="GitHub - Tuks-ICMM/Pharmacogenetic-Analysis-Pipeline: A Snakemake powered pipeline developed to perform variant-effect-prediction, frequency analysis and Admixture analysis given multiple Variant Call Format datasets. This has been developed in partial fulfilment of a MSc in Bioinformatics at the University of Pretoria by Graeme Ford.">
 <meta name="twitter:description"