Fix typos and broken links

GenomicsAotearoa · Sep 2, 2023 · 08a07c5 · 08a07c5
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diff --git a/docs/day3/ex10_viruses.md b/docs/day3/ex10_viruses.md
@@ -3,7 +3,7 @@
 !!! info "Objectives"
 
     * [Identifying viral contigs](#identifying-viral-contigs)
-    * [Identifying viral contigs using `VirSorter2`](#identifying-viral-contigs-using-VirSorter2)
+    * [Identifying viral contigs using `VirSorter2`](#identifying-viral-contigs-using-virsorter2)
     * [Checking quality and estimating completeness of the viral contigs via `CheckV`](#checking-quality-and-estimate-completeness-of-the-viral-contigs-via-checkv)
     * [Exercise: Examining viral output files from `VirSorter2` and `CheckV`](#exercise-examining-viral-output-files-from-virsorter2-and-checkv)
     * [Introduction to `vConTACT2` for predicting taxonomy of viral contigs](#introduction-to-vcontact2-for-predicting-taxonomy-of-viral-contigs)
@@ -207,9 +207,9 @@ A few notes to consider:
     * You will see that the `genome_by_genome_overview.csv` file contains entries for the full reference database used as well as the input viral contigs (contigs starting with `NODE`). 
     * You can use a command such as `grep "NODE" vConTACT2_Results/genome_by_genome_overview.csv | less` to view only the lines for the input contigs of interest. 
         * Note also that these lines however will *not* contain taxonomy information. 
-        * See the notes in the [Appendix](https://github.com/GenomicsAotearoa/metagenomics_summer_school/blob/master/materials/resources/APPENDIX_ex11_viral_taxonomy_prediction_via_vContact2.md) for further information about why this might be.
+        * See the notes in the [Appendix](../resources/4_APPENDIX_ex11_viral_taxonomy_prediction_via_vContact2.md) for further information about why this might be.
         
-    * As per the notes in the [Appendix](https://github.com/GenomicsAotearoa/metagenomics_summer_school/blob/master/materials/resources/APPENDIX_ex11_viral_taxonomy_prediction_via_vContact2.md), the `tax_predict_table.tsv` file contains *predictions* of potential taxonomy (and or *taxonomies*) of the input viral contigs for order, family, and genus, based on whether they clustered with any viruses in the reference database.
+    * As per the notes in the [Appendix](../resources/4_APPENDIX_ex11_viral_taxonomy_prediction_via_vContact2.md), the `tax_predict_table.tsv` file contains *predictions* of potential taxonomy (and or *taxonomies*) of the input viral contigs for order, family, and genus, based on whether they clustered with any viruses in the reference database.
         * Note that these may be lists of *multiple* potential taxonomies, in the cases where viral contigs clustered with multiple reference viruses representing more than one taxonomy at the given rank.
 
         !!! note "" 

diff --git a/docs/day3/ex11.1_phylogenomics.md b/docs/day3/ex11.1_phylogenomics.md
@@ -167,4 +167,4 @@ We can edit and add annotations by clicking within the iTol website environment.
 
     [Kapli, P., Yang, Z. and Telford M.J. (2020) Phylogenetic tree building in the genomic age. Nat Rev Genet 21: 428-444](https://doi.org/10.1038/s41576-020-0233-0)
 
-    [Yang, Z. and Rannala, B. (2012) Molecular phylogenetics: principles and practice. Nat Rev Genet 13: 303-314.](https://doi-org.ezproxy.auckland.ac.nz/10.1038/nrg3186)
+    [Yang, Z. and Rannala, B. (2012) Molecular phylogenetics: principles and practice. Nat Rev Genet 13: 303-314.](https://doi.org/10.1038/nrg3186)
diff --git a/docs/day3/ex14_gene_annotation_part2.md b/docs/day3/ex14_gene_annotation_part2.md
@@ -444,6 +444,6 @@ Depending on what you are looking for, you will either be trying to find gene(s)
 
 To conduct this exersise, you should use the information generated with `DRAM` as well as the annotation files we created previously that will be available in the directory `10.gene_annotation_and_coverage/gene_annotations`. 
 
-Please note that we have also provided further annotation files within the directory `10.gene_annotation_and_coverage/example_annotation_tables` that contain information obtained after annotating the MAGs against additional databases (UniProt, UniRef100, KEGG, PFAM and TIGRfam). These example files can also be downloaded from [here](../resources/example_annotation_tables.zip). These files were created by using an in-house python script designed to aggregate different annotations and as part of the environmental metagenomics worflow followed in Handley's lab. Information about using this script as well as the script is available [here](https://github.com/GenomicsAotearoa/environmental_metagenomics/blob/master/metagenomic_annotation/3.aggregation.md)  
+Please note that we have also provided further annotation files within the directory `10.gene_annotation_and_coverage/example_annotation_tables` that contain information obtained after annotating the MAGs against additional databases (UniProt, UniRef100, KEGG, PFAM and TIGRfam). These example files can also be downloaded from [here](../resources/example_annotation_tables.zip). These files were created by using an in-house python script designed to aggregate different annotations and as part of the environmental metagenomics worflow followed in Handley's lab. Information about using this script as well as the script is available [here](https://github.com/GenomicsAotearoa/environmental_metagenomics/blob/master/old_stuff/metagenomic_annotation/3.aggregation.md)  
 
 ---
diff --git a/docs/day4/ex16a_data_presentation_Intro.md b/docs/day4/ex16a_data_presentation_Intro.md
@@ -26,7 +26,7 @@ As the fundamental point of data visualisation is *communication*, when building
 * [ColorBrewer2](https://colorbrewer2.org/#type=sequential&scheme=BuGn&n=3) (select 'colorblindsafe')
 * [chroma.js](https://gka.github.io/palettes/#/7|d|6e5300,7c8c00,00a63e|ffffe0,ff005e,93003a|1|1)
 * Selecting and checking your colour choice using [Viz Palette](https://projects.susielu.com/viz-palette?colors=[%22#ffd700%22,%22#ffb14e%22,%22#fa8775%22,%22#ea5f94%22,%22#cd34b5%22,%22#9d02d7%22,%22#0000ff%22]&backgroundColor=%22white%22&fontColor=%22black%22&mode=%22achromatopsia%22)
-* [Blog post](https://bconnelly.net/posts/creating_colorblind-friendly_figures/) by Brian Connelly.
+* [An article featuring tips for visual accessibility](https://www.nature.com/articles/d41586-021-02696-z)
 * Several useful colour palettes designed by Martin Krzywinski are available [here](http://mkweb.bcgsc.ca/colorblind/palettes.mhtml#page-container)
 * [Stack Overflow community suggestions](https://stackoverflow.com/questions/57153428/r-plot-color-combinations-that-are-colorblind-accessible)
 

diff --git a/docs/resources/4_APPENDIX_ex11_viral_taxonomy_prediction_via_vContact2.md b/docs/resources/4_APPENDIX_ex11_viral_taxonomy_prediction_via_vContact2.md
@@ -21,6 +21,7 @@ Example slurm script:
 
     #SBATCH --account       nesi02659
     #SBATCH --job-name      prodigal
+    #SBATCH --partition     milan
     #SBATCH --time          00:05:00
     #SBATCH --mem           1GB
     #SBATCH --cpus-per-task 2
@@ -113,6 +114,7 @@ Use `vContact2`'s `vcontact2_gene2genome` script to generate the required mappin
 From the `vContact2` online docs:
 
 !!! quote ""
+
     One important note is that the taxonomic information is not included for user sequences. This means that each user will need to find their genome(s) of interest and check to see if reference genomes are located in the same VC. If the user genome is within the same VC sub-cluster as a reference genome, then there's a very high probability that the user genome is part of the same genus. If the user genome is in the same VC but not the same sub-cluster as a reference, then it's highly likely the two genomes are related at roughly genus-subfamily level. If there are no reference genomes in the same VC or VC sub-cluster, then it's likely that they are not related at the genus level at all.
 
 The summary output of `vContact2` is the file `vConTACT2_Results/genome_by_genome_overview.csv`. As the comment above notes, one approach would be to search this file for particular contigs of interest, and see if any reference genomes fall into the same viral cluster (VC), using this reference to predict the taxonomy of the contig of interest.