Update tutorial.qmd

minor edits

tutorial.qmd

@@ -13,7 +13,7 @@ Before starting, first take a look at the Quickstart for instructions on how to
 
 ## Example 1: Standard Run
 
-This example uses sequencing reads from an 2022 outbreak of *Xanthomonas hortorum* across several plant nurseries. Using whole-genome sequencing, researchers determined a shared genetic basis between strains at different locations. With this information, they traced the origin of the outbreak to a single supplier that sold infected cuttings. You can read more about the study <a href="https://doi.org/10.1094/PHYTO-09-22-0321-R" target="_blank">here. </a> 
+This example uses sequencing reads from an 2022 outbreak of the bacterial pathogen *Xanthomonas hortorum* found infecting geranium in several plant nurseries. Using whole-genome sequencing, researchers determined a shared genetic basis between strains at different locations. With this information, they traced the origin of the outbreak to a single supplier that sold infected cuttings. You can read more about the study <a href="https://doi.org/10.1094/PHYTO-09-22-0321-R" target="_blank">here. </a> 
 
 We'll be treating the pathogen as an unknown and using the pathogensurveillance pipeline to determine what we know already (that these samples come from *Xanthomonas hortorum*). We'll also see the high degree of shared DNA sequence between samples, which is seen from several plots that the pathogensurveillance pipeline generates automatically. <br/>
 
@@ -54,7 +54,7 @@ nextflow run nf-core/pathogensurveillance --sample_data https://raw.githubuserco
 
 When running your own analysis, you will need to provide your own path to the input CSV file.
 
-By default, the pipeline will run on 128 GB of RAM and 16 threads. This is more resources than is strictly necessary and beyond the capacity of most desktop computers. We can scale this back a bit for this lightweight test run. This analysis will work with 8 cpus and 30 GB of RAM (albeit more slowly), which is specified by the --max_cpus and --max_memory settings.
+By default, the pipeline will run on 128 GB of RAM and 16 threads. These are more resources than are strictly necessary and beyond the capacity of most desktop computers. We can scale this back a bit for this lightweight test run. This analysis will work with 8 CPUs and 30 GB of RAM (albeit more slowly), which is specified by the --max_cpus and --max_memory settings.
 
 The setting `-resume` is only necessary when resuming a previous analysis. However, it doesn't hurt to include it at the start. If the pipeline is interrupted, this setting allows progress to pick up where it left off – as long as the previous command is executed from the same working directory.
 
@@ -232,4 +232,4 @@ df |> head()
 The path to this reference csv needs to be specified in the command to run the pipeline:
 ``` bash
 nextflow run nf-core/pathogensurveillance --sample_data mycobacterium_samples.csv --reference_input mycobacterium_references.csv --out_dir mycobacterium_test --download_bakta_db true -profile docker 
-```
+```