[Documentation] fix broken links, update syntax, improvements to thei…

…ameta page (#720)

* clarify

* update memory requirement for task

* fix broken links

* fix typo

* standardize syntax

* finish updating theiameta

* fix typo

docs/workflows/genomic_characterization/freyja.md

@@ -552,8 +552,6 @@ The main requirement to run Freyja on other pathogens is **the existence of a ba
 
 The appropriate barcode file and reference sequence need to be downloaded and uploaded to your [Terra.bio](http://Terra.bio) workspace.
 
-
-
 When running **Freyja_FASTQ_PHB**, the appropriate reference and barcodes file need to be passed as inputs. The first is a required input and will show up at the top of the workflows inputs page on [Terra.bio](http://Terra.bio) ([Figure 2](freyja.md/#figure2)).
 
 !!! caption "Figure 2:  Required input for Freyja_FASTQ_PHB to provide the reference genome to be used by Freyja"

docs/workflows/genomic_characterization/theiaeuk.md

@@ -322,8 +322,8 @@ All input reads are processed through "core tasks" in the TheiaEuk workflows. Th
 
     De Novo assembly will be undertaken only for samples that have sufficient read quantity and quality, as determined by the `screen` task assessment of clean reads. 
 
-    In TheiaEuk, assembly is performed using the [Shovill](https://github.com/tseemann/shovill) pipeline. This undertakes the assembly with one of four assemblers ([SKESA](https://github.com/ncbi/SKESA) (default), [SPAdes](https://github.com/ablab/spades), [Velvet](https://github.com/dzerbino/velvet/), [Megahit](https://github.com/voutcn/megahit)), but also performs [a number of pre- and post-processing steps](https://github.com/tseemann/shovill#main-steps) to improve the resulting genome assembly. Shovill uses an estimated genome size (see [here](https://github.com/tseemann/shovill#--gsize)). If this is not provided by the user as an optional input, Shovill will estimate the genome size using [mash](https://mash.readthedocs.io/en/latest/index.html). Adaptor trimming can be undertaken with Shovill by setting the `trim` option to "true", but this is set to "false" by default as [alternative adapter trimming](https://www.notion.so/TheiaProk-Workflow-Series-89b9c08406094ec78d08a578fe861626?pvs=21) is undertaken in the TheiaEuk workflow.
-
+    In TheiaEuk, assembly is performed using the [Shovill](https://github.com/tseemann/shovill) pipeline. This undertakes the assembly with one of four assemblers ([SKESA](https://github.com/ncbi/SKESA) (default), [SPAdes](https://github.com/ablab/spades), [Velvet](https://github.com/dzerbino/velvet/), [Megahit](https://github.com/voutcn/megahit)), but also performs [a number of pre- and post-processing steps](https://github.com/tseemann/shovill#main-steps) to improve the resulting genome assembly. Shovill uses an estimated genome size (see [here](https://github.com/tseemann/shovill#--gsize)). If this is not provided by the user as an optional input, Shovill will estimate the genome size using [mash](https://mash.readthedocs.io/en/latest/index.html). Adaptor trimming can be undertaken with Shovill by setting the `trim` option to "true", but this is set to "false" by default as alternative adapter trimming performed by bbduk is undertaken in the TheiaEuk workflow.
+    
     ??? toggle "What is _de novo_  assembly?"
         _De novo_  assembly is the process or product of attempting to reconstruct a genome from scratch (without prior knowledge of the genome) using sequence reads. Assembly of fungal genomes from short-reads will produce multiple contigs per chromosome rather than a single contiguous sequence for each chromosome.
         

docs/workflows/phylogenetic_construction/core_gene_snp.md

@@ -128,8 +128,8 @@ By default, this task appends a Phandango coloring tag to color all items from t
 
 ## References
 
->Sion C Bayliss, Harry A Thorpe, Nicola M Coyle, Samuel K Sheppard, Edward J Feil, PIRATE: A fast and scalable pangenomics toolbox for clustering diverged orthologues in bacteria, *GigaScience*, Volume 8, Issue 10, October 2019, giz119, <https://doi.org/10.1093/gigascience/giz119>
+>Sion C Bayliss, Harry A Thorpe, Nicola M Coyle, Samuel K Sheppard, Edward J Feil, PIRATE: A fast and scalable pangenomics toolbox for clustering diverged orthologues in bacteria, _GigaScience_, Volume 8, Issue 10, October 2019, giz119, <https://doi.org/10.1093/gigascience/giz119>
 <!-- -->
-> Lam-Tung Nguyen, Heiko A. Schmidt, Arndt von Haeseler, Bui Quang Minh, IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies, *Molecular Biology and Evolution*, Volume 32, Issue 1, January 2015, Pages 268–274, <https://doi.org/10.1093/molbev/msu300>
+> Lam-Tung Nguyen, Heiko A. Schmidt, Arndt von Haeseler, Bui Quang Minh, IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies, _Molecular Biology and Evolution_, Volume 32, Issue 1, January 2015, Pages 268–274, <https://doi.org/10.1093/molbev/msu300>
 <!-- -->
 > <https://github.com/tseemann/snp-dists>

docs/workflows/phylogenetic_construction/ksnp3.md

@@ -119,6 +119,6 @@ If you fill out the `data_summary_*` and `sample_names` optional variables, you
 
 ## References
 
->Shea N Gardner, Tom Slezak, Barry G. Hall, kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome, *Bioinformatics*, Volume 31, Issue 17, 1 September 2015, Pages 2877–2878, <https://doi.org/10.1093/bioinformatics/btv271>
+>Shea N Gardner, Tom Slezak, Barry G. Hall, kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome, _Bioinformatics_, Volume 31, Issue 17, 1 September 2015, Pages 2877–2878, <https://doi.org/10.1093/bioinformatics/btv271>
 <!-- -->
 <https://github.com/tseemann/snp-dists>

docs/workflows/phylogenetic_construction/snippy_streamline.md

@@ -228,7 +228,7 @@ For all cases:
 | snippy_filtered_metadata | File | TSV recording the columns of the Terra data table that were used in the summarize_data task |
 | snippy_final_alignment | File | Final alignment (FASTA file) used to generate the tree (either after snippy alignment, gubbins recombination removal, and/or core site selection with SNP-sites) |
 | snippy_final_tree | File | Final phylogenetic tree produced by Snippy_Streamline |
-| snippy_gubbins_branch_stats | File | CSV file showing <https://github.com/nickjcroucher/gubbins/blob/master/docs/gubbins_manual.md#output-statistics >for each branch of the tree   |
+| snippy_gubbins_branch_stats | File | CSV file showing <https://github.com/nickjcroucher/gubbins/blob/master/docs/gubbins_manual.md#output-statistics> for each branch of the tree   |
 | snippy_gubbins_docker | String | Docker file used for Gubbins |
 | snippy_gubbins_recombination_gff | File | Recombination statistics in GFF format; these can be viewed in Phandango against the phylogenetic tree |
 | snippy_gubbins_version | String | Gubbins version used |
@@ -261,4 +261,4 @@ For all cases:
 | snippy_variants_snippy_version | Array[String] | Version of Snippy_Tree subworkflow used |
 | snippy_wg_snp_matrix | File | CSV file of whole genome pairwise SNP distances between samples, calculated from the final alignment |
 
-</div>
+</div>

docs/workflows/phylogenetic_construction/snippy_tree.md

@@ -356,7 +356,7 @@ Sequencing data used in the Snippy_Tree workflow must:
 | snippy_filtered_metadata | File | TSV recording the columns of the Terra data table that were used in the summarize_data task |
 | snippy_final_alignment | File | Final alignment (FASTA file) used to generate the tree (either after snippy alignment, gubbins recombination removal, and/or core site selection with SNP-sites) |
 | snippy_final_tree | File | Newick tree produced from the final alignment. Depending on user input for core_genome, the tree could be a core genome tree (default when core_genome is true) or whole genome tree (if core_genome is false) |
-| snippy_gubbins_branch_stats | File | CSV file showing https://github.com/nickjcroucher/gubbins/blob/master/docs/gubbins_manual.md#output-statistics for each branch of the tree   |
+| snippy_gubbins_branch_stats | File | CSV file showing <https://github.com/nickjcroucher/gubbins/blob/master/docs/gubbins_manual.md#output-statistics> for each branch of the tree   |
 | snippy_gubbins_docker | String | Docker file used for running Gubbins |
 | snippy_gubbins_recombination_gff | File | Recombination statistics in GFF format; these can be viewed in Phandango against the phylogenetic tree |
 | snippy_gubbins_version | String | Gubbins version used |

docs/workflows/standalone/kraken2.md

@@ -10,7 +10,7 @@
 
 **The Kraken2 workflows assess the taxonomic profile of raw sequencing data (FASTQ files).**
 
-Kraken2 is a bioinformatics tool originally designed for metagenomic applications. It has additionally proven valuable for validating taxonomic assignments and checking contamination of single-species (e.g. bacterial isolate, eukaryotic isolate, viral isolate, etc.) whole genome sequence data. 
+Kraken2 is a bioinformatics tool originally designed for metagenomic applications. It has additionally proven valuable for validating taxonomic assignments and checking contamination of single-species (e.g. bacterial isolate, eukaryotic isolate, viral isolate, etc.) whole genome sequence data.
 
 There are three Kraken2 workflows:
 
@@ -35,12 +35,12 @@ Besides the data input types, there are minimal differences between these two wo
 | Database name | Database Description | Suggested Applications | GCP URI (for usage in Terra) | Source | Database Size (GB) | Date of Last Update |
 | --- | --- | --- | --- | --- | --- | --- |
 | **Kalamari v5.1** | Kalamari is a database of complete public assemblies, that has been fine-tuned for enteric pathogens and is backed by trusted institutions. [Full list available here ( in chromosomes.tsv and plasmids.tsv)](https://github.com/lskatz/Kalamari/tree/master/src) | Single-isolate enteric bacterial pathogen analysis (Salmonella, Escherichia, Shigella, Listeria, Campylobacter, Vibrio, Yersinia) | **`gs://theiagen-large-public-files-rp/terra/databases/kraken2/kraken2.kalamari_5.1.tar.gz`** | ‣ | 1.5 | 18/5/2022 |
-| **standard 8GB** | Standard RefSeq database (archaea, bacteria, viral, plasmid, human, UniVec_Core) capped at 8GB | Prokaryotic or viral organisms, but for enteric pathogens, we recommend Kalamari | **`gs://theiagen-large-public-files-rp/terra/databases/kraken2/k2_standard_08gb_20240112.tar.gz`** | https://benlangmead.github.io/aws-indexes/k2 | 7.5 | 12/1/2024 |
-| **standard 16GB** | Standard RefSeq database (archaea, bacteria, viral, plasmid, human, UniVec_Core) capped at 16GB | Prokaryotic or viral organisms, but for enteric pathogens, we recommend Kalamari | **`gs://theiagen-large-public-files-rp/terra/databases/kraken2/k2_standard_16gb_20240112.tar.gz`** | https://benlangmead.github.io/aws-indexes/k2 | 15 | 12/1/2024 |
-| **standard** | Standard RefSeq database (archaea, bacteria, viral, plasmid, human, UniVec_Core)  | Prokaryotic or viral organisms, but for enteric pathogens, we recommend Kalamari | **`gs://theiagen-large-public-files-rp/terra/databases/kraken2/k2_standard_20240112.tar.gz`** | https://benlangmead.github.io/aws-indexes/k2 | 72 | 18/4/2023 |
-| **viral** | RefSeq viral | Viral metagenomics | **`gs://theiagen-large-public-files-rp/terra/databases/kraken2/k2_viral_20240112.tar.gz`** | https://benlangmead.github.io/aws-indexes/k2 | 0.6 | 12/1/2024 |
-| **EuPathDB48** | Eukaryotic pathogen genomes with contaminants removed. [Full list available here](https://genome-idx.s3.amazonaws.com/kraken/k2_eupathdb48_20201113/EuPathDB48_Contents.txt) | Eukaryotic organisms (Candida spp., Aspergillus spp., etc) | **`gs://theiagen-public-files-rp/terra/theiaprok-files/k2_eupathdb48_20201113.tar.gz`** | https://benlangmead.github.io/aws-indexes/k2 | 30.3 | 13/11/2020 |
-| **EuPathDB48** | Eukaryotic pathogen genomes with contaminants removed. [Full list available here](https://genome-idx.s3.amazonaws.com/kraken/k2_eupathdb48_20201113/EuPathDB48_Contents.txt) | Eukaryotic organisms (Candida spp., Aspergillus spp., etc) | **`gs://theiagen-large-public-files-rp/terra/databases/kraken/k2_eupathdb48_20230407.tar.gz`** | https://benlangmead.github.io/aws-indexes/k2 | 11 | 7/4/2023 |
+| **standard 8GB** | Standard RefSeq database (archaea, bacteria, viral, plasmid, human, UniVec_Core) capped at 8GB | Prokaryotic or viral organisms, but for enteric pathogens, we recommend Kalamari | **`gs://theiagen-large-public-files-rp/terra/databases/kraken2/k2_standard_08gb_20240112.tar.gz`** | <https://benlangmead.github.io/aws-indexes/k2> | 7.5 | 12/1/2024 |
+| **standard 16GB** | Standard RefSeq database (archaea, bacteria, viral, plasmid, human, UniVec_Core) capped at 16GB | Prokaryotic or viral organisms, but for enteric pathogens, we recommend Kalamari | **`gs://theiagen-large-public-files-rp/terra/databases/kraken2/k2_standard_16gb_20240112.tar.gz`** | <https://benlangmead.github.io/aws-indexes/k2> | 15 | 12/1/2024 |
+| **standard** | Standard RefSeq database (archaea, bacteria, viral, plasmid, human, UniVec_Core)  | Prokaryotic or viral organisms, but for enteric pathogens, we recommend Kalamari | **`gs://theiagen-large-public-files-rp/terra/databases/kraken2/k2_standard_20240112.tar.gz`** | <https://benlangmead.github.io/aws-indexes/k2> | 72 | 18/4/2023 |
+| **viral** | RefSeq viral | Viral metagenomics | **`gs://theiagen-large-public-files-rp/terra/databases/kraken2/k2_viral_20240112.tar.gz`** | <https://benlangmead.github.io/aws-indexes/k2> | 0.6 | 12/1/2024 |
+| **EuPathDB48** | Eukaryotic pathogen genomes with contaminants removed. [Full list available here](https://genome-idx.s3.amazonaws.com/kraken/k2_eupathdb48_20201113/EuPathDB48_Contents.txt) | Eukaryotic organisms (Candida spp., Aspergillus spp., etc) | **`gs://theiagen-public-files-rp/terra/theiaprok-files/k2_eupathdb48_20201113.tar.gz`** | <https://benlangmead.github.io/aws-indexes/k2> | 30.3 | 13/11/2020 |
+| **EuPathDB48** | Eukaryotic pathogen genomes with contaminants removed. [Full list available here](https://genome-idx.s3.amazonaws.com/kraken/k2_eupathdb48_20201113/EuPathDB48_Contents.txt) | Eukaryotic organisms (Candida spp., Aspergillus spp., etc) | **`gs://theiagen-large-public-files-rp/terra/databases/kraken/k2_eupathdb48_20230407.tar.gz`** | <https://benlangmead.github.io/aws-indexes/k2> | 11 | 7/4/2023 |
 
 </div>
 
@@ -158,4 +158,4 @@ Krona will only output hierarchical results for bacterial organisms in its curre
     | --- | --- |
     | Software Source Code | [Kraken2 on GitHub](https://github.com/DerrickWood/kraken2/)  |
     | Software Documentation | <https://github.com/DerrickWood/kraken2/blob/master/docs/MANUAL.markdown> |
-    | Original Publication(s) | [Improved metagenomic analysis with Kraken 2](https://link.springer.com/article/10.1186/s13059-019-1891-0) |
+    | Original Publication(s) | [Improved metagenomic analysis with Kraken 2](https://link.springer.com/article/10.1186/s13059-019-1891-0) |

docs/workflows/standalone/ncbi_amrfinderplus.md

@@ -66,4 +66,4 @@ You can check if a gene or point mutation is in the AMRFinderPlus database [here
 
 >Feldgarden M, Brover V, Gonzalez-Escalona N, Frye JG, Haendiges J, Haft DH, Hoffmann M, Pettengill JB, Prasad AB, Tillman GE, Tyson GH, Klimke W. AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence. Sci Rep. 2021 Jun 16;11(1):12728. doi: 10.1038/s41598-021-91456-0. PMID: 34135355; PMCID: PMC8208984. <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208984/>
 <!-- -->
-><https://github.com/ncbi/amr>
+><https://github.com/ncbi/amr>

docs/workflows/standalone/ncbi_scrub.md

@@ -89,4 +89,4 @@ This workflow is composed of two tasks, one to dehost the input reads and anothe
 | read1_dehosted | File | Dehosted forward reads | PE, SE |
 | read2_dehosted | File | Dehosted reverse reads | PE |
 
-</div>
+</div>

docs/workflows/standalone/theiavalidate.md

@@ -163,4 +163,4 @@ If the above inputs are provided, then the following output files will be genera
 
 [example_exact_differences.tsv](../../assets/files/theiavalidate/example_exact_differences.tsv)
 
-[example_validation_criteria_differences.tsv](../../assets/files/theiavalidate/example_validation_criteria_differences.tsv)
+[example_validation_criteria_differences.tsv](../../assets/files/theiavalidate/example_validation_criteria_differences.tsv)

tasks/phylogenetic_inference/utilities/task_snp_sites.wdl

@@ -13,7 +13,7 @@ task snp_sites {
     String docker = "us-docker.pkg.dev/general-theiagen/staphb/snp-sites:2.5.1"
     Int disk_size = 100
     Int cpu = 1
-    Int memory = 4
+    Int memory = 2
   }
   command <<< 
     snp-sites -V > VERSION