update ww materials

materials/01-intro/02-ngs.md

@@ -129,7 +129,7 @@ zcat sequences.fq.gz | wc -l
 If we want to know how many sequences there are in the file, we can divide the result by 4 (since each sequence is always represented across four lines).
 
 
-### FASTQ Quality Control
+### FASTQ Quality Control {#sec-fastqc}
 
 One of the most basic tasks in Illumina sequence analysis is to run a quality control step on the FASTQ files we obtained from the sequencing machine. 
 

materials/02-isolates/02-qc.md

@@ -55,13 +55,13 @@ This table also contains information about the lineage/clade assigned to each sa
 This gives us an idea of which samples may be more similar to each other, and where they fit in the global context of other sequences available publicly.
 We will talk more about this topic in the [lineage assignment section](03-lineages.md). 
 
-:::{.callout-warning}
+<!-- :::{.callout-warning}
 #### Lineage Versions
 
 Although the _Viralrecon_ pipeline runs _Pangolin_ and _Nextclade_ to perform lineage assignment, it does not use the latest version of these programs (because lineages evolve so fast, the nomenclature constantly changes). 
 Therefore, this information should mostly be ignored at this stage, and instead we should run our analysis on the most up-to-date versions of these programs. 
 We will detail this in the [Lineages and Variants](03-lineages.md) section of the materials. 
-:::
+::: -->
 
 ![Snapshot of the "Variant Metrics" section of the `viralrecon` _MultiQC_ report. Simple scatterplots can be made from the data on this table using the <kbd>Plot</kbd> button. For example, at the bottom we show a scatterplot showing the relationship between the median depth of coverage and the number of ambiguous bases 'N' per 100kb. For the data in this example, we can see that when the average depth of coverage drops below around 200 reads we start getting higher number of missing bases in the assembly.](images/viralrecon_multiqc_variant_metrics.svg)
 
@@ -78,7 +78,7 @@ It can mean two things:
 :::
 
 
-### Amplicon Depth of Coverage
+### Amplicon Depth of Coverage {#sec-amplicon-coverage}
 
 The next section of the report - **Amplicon Coverage Heatmap** - contains a graphical representation of the average depth of coverage for each PCR amplicon in the ARTIC protocol (i.e. the average number of reads mapped to each amplicon interval). 
 This plot is extremely useful to identify common PCR dropouts occurring across many samples. 

materials/04-wastewater/01-ww_surveillance.md

@@ -55,6 +55,11 @@ Different methods may work better or worse for different samples and situations.
 Also depends on resources available (equipment and reagents). 
 
 
+## Metadata
+
+See https://github.com/pha4ge/Wastewater_Contextual_Data_Specification?tab=readme-ov-file
+
+
 ## Glossary
 
 - WBE - wastewater-based epidemiology