Added DADA2 pipelines and modified documentation

Documentation now is correct for Raw data processing as previously missing DADA2 pipelines were added.

README.md

@@ -9,7 +9,7 @@ The repository includes the following contents:
 
 1. **'analysis' folder**: contains scripts and intermediary files used and generated in the analysis.
 Analysis was largely conducted per primer used in metabarcoding and then synthesized in some higher level analyses.
-For each primer pair, the following is provided
+For each primer pair (marker), the following is provided
    - R script for the metabarcoding data analysis, including data preprocessing, diversity analysis, and statistical testing.
    - Intermediary metabarcoding data, including amplicon sequence variants (ASVs), taxonomy, ASV counts for each sample and DADA2 processing logs.
    - Metadata for the samples, including NDVI, and other relevant variables.
@@ -28,11 +28,13 @@ For each primer pair, the following is provided
    git clone https://gitlab.nibio.no/simeon/persdatter-et-al-2025-metabarcoding.git
    ```
 
-2. Ensure you have the necessary R packages installed. All necessary dependencies required by the analysis scripts are listed in the top chunks of the respective scripts.
+2. Optional: Obtain the raw read data from [SRA](https://www.ncbi.nlm.nih.gov/bioproject/) under the BioProject with the accession PRJNA1191665. 
+Run the DADA2 scripts in `/analysis/raw_read_processing`. This will re-generate the intermediate data from raw reads. The intermediate data is 
+already contained in each of the marker directories, e.g. `/analysis/16S/16S_DADA2_results_260821`.
 
-3. Obtain the raw read data from [SRA](https://www.ncbi.nlm.nih.gov/bioproject/) under the BioProject with the accession PRJNA1191665.
+3. Ensure you have the necessary R packages installed. All necessary dependencies required by the analysis scripts are listed in the top chunks of the respective scripts.
 
-4. Open the R Markdown file and run the code to reproduce the metabarcoding data analysis.
+4. Open the R Markdown file contained in each of the marker directories, e.g. `/analysis/16S/16S_DADA2_results_260821` to reproduce the metabarcoding data analysis.
 
 ## Citing this Repository