updating README + show_supported_models fix

README.md

@@ -16,6 +16,17 @@
 **nf-core/epitopeprediction** is a bioinformatics best-practice analysis pipeline for epitope prediction and annotation.
 The pipeline performs epitope predictions for a given set of variants or peptides directly using state of the art prediction tools. Additionally, resulting prediction results can be annotated with metadata.
 
+Supported prediction tools:
+
+- `syfpeithi`
+- `mhcflurry`
+- `mhcnuggets-class-1`
+- `mhcnuggets-class-2`
+- `netmhcpan-4.0`
+- `netmhcpan-4.1`
+- `netmhc-4.0`
+- `netmhciipan-4.1`
+
 The pipeline is built using [Nextflow](https://www.nextflow.io), a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The [Nextflow DSL2](https://www.nextflow.io/docs/latest/dsl2.html) implementation of this pipeline uses one container per process which makes it easier to maintain and update software dependencies. Where possible, these processes have been submitted to and installed from [nf-core/modules](https://github.com/nf-core/modules) in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!
 
 On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources.The results obtained from the full-sized test can be viewed on the [nf-core website](https://nf-co.re/epitopeprediction/results).

workflows/epitopeprediction.nf

@@ -180,14 +180,14 @@ workflow EPITOPEPREDICTION {
 
     // TODO I guess it would be better to have two subworkflows for the if else parts (CM)
     if (params.show_supported_models) {
-        SHOW_SUPPORTED_MODELS(
+        EPYTOPE_SHOW_SUPPORTED_MODELS(
             ch_samples_uncompressed
                 .protein
                 .mix(ch_samples_uncompressed.variant, ch_samples_uncompressed.peptide)
                 .combine(ch_prediction_tool_versions)
                 .first()
         )
-        ch_versions = ch_versions.mix(SHOW_SUPPORTED_MODELS.out.versions)
+        ch_versions = ch_versions.mix(EPYTOPE_SHOW_SUPPORTED_MODELS.out.versions)
     }
 
     else {