Restore description

config/description.md

@@ -1,14 +1,13 @@
-**Forecasts:** For H3N2 only, the frequency panel shows projections of currently circulating strain frequencies one year into the future in one month intervals. Frequency projections are calculated from a previously trained fitness model based on the current frequency and estimated fitness of each strain as described in [Huddleston et al (2020, eLife)](https://elifesciences.org/articles/60067). We estimate strain fitness by a combination of antigenic novelty and mutational load. Antigenic novelty (available as the coloring "HI antigenic novelty") is based on inferred measurements of antigenic advance from hemaggluttination inhibition (HI) assays. Mutational load (available as the coloring "Mutational load") is the number of amino acid mutations each strain carries at putative non-epitope sites relative to its most recent ancestor from the previous season.
 
-We thank the [GISAID Initiative](https://gisaid.org) and the [GISRS Network](http://www.who.int/influenza/gisrs_laboratory/en/) for critical surveillance efforts and open data sharing. Titer data used in antigenic analyses was generated by the [Influenza Division at the US Centers for Disease Control and Prevention](https://www.cdc.gov/flu/), the [Worldwide Influenza Centre at the Francis Crick Institute](http://www.crick.ac.uk/research/worldwide-influenza-centre), the [Victorian Infectious Diseases Reference Laboratory at the Australian Peter Doherty Institute for Infection and Immunity](http://www.vidrl.org.au/) and the [Influenza Virus Research Center at the Japan National Institute of Infectious Diseases](https://www.niid.go.jp/niid/en/flu-e.html). We gratefully acknowledge the authors, originating and submitting laboratories of sequences from the GISAID EpiFlu Database on which this research is based. An attribution table is available by clicking on "Download Data" at the bottom of the page and then clicking on "Strain Metadata" in the resulting dialog box.
+We thank the [GISAID Initiative](https://gisaid.org) and the [GISRS Network](https://www.who.int/initiatives/global-influenza-surveillance-and-response-system) for critical surveillance efforts and open data sharing. Titer data used in antigenic analyses was generated by the [Influenza Division at the US Centers for Disease Control and Prevention](https://www.cdc.gov/flu/), the [Worldwide Influenza Centre at the Francis Crick Institute](http://www.crick.ac.uk/research/worldwide-influenza-centre), the [Victorian Infectious Diseases Reference Laboratory at the Australian Peter Doherty Institute for Infection and Immunity](http://www.vidrl.org.au/) and the [Influenza Virus Research Center at the Japan National Institute of Infectious Diseases](https://www.niid.go.jp/niid/en/flu-e.html). We gratefully acknowledge the authors, originating and submitting laboratories of sequences from the GISAID EpiFlu Database on which this research is based. An attribution table is available by clicking on "Download Data" at the bottom of the page and then clicking on "Acknowledgments" in the resulting dialog box.
 
 Special thanks to Jackie Katz, Dave Wentworth, Becky Kondor, Vivien Dugan, Xiyan Xu, Elizabeth Neuhaus, Sujatha Seenu, John McCauley, Rod Daniels, Vicki Gregory, Kanta Subbarao, Ian Barr, Aeron Hurt, Takato Odagiri, Shinji Watanabe, Tomoko Kuwahara, Michael Lässig, Marta Łuksza, Richard Reeve, Colin Russell, Sebastian Maurer-Stroh and Peter Bogner for feedback and advice. This analysis represents an updated frontend to the Nextflu informatic pipeline, originally available at nextflu.org.
 
 <div>
     <a href="https://gisaid.org">
         <img alt="gisaid-logo" width="120" src="https://www.gisaid.org/fileadmin/gisaid/img/schild.png"/>
     </a>
-    <a href="http://www.who.int/influenza/gisrs_laboratory/en/">
+    <a href="https://www.who.int/initiatives/global-influenza-surveillance-and-response-system">
         <img alt="gisrs-logo" width="120" src="https://www.who.int/images/default-source/departments/global-influenza-programme/gisrs-insignia-no-tagline-full-colour4cbbe30db0a548ab9795c48b748ef921.tmb-1920v.jpg"/>
     </a>
 </div>

profiles/nextflu-private/antigenic_distances.smk

@@ -172,6 +172,7 @@ rule export_private:
         node_data = _get_node_data_by_wildcards,
         private_node_data = get_private_node_data,
         auspice_config = lambda w: config['builds'][w.build_name]['auspice_config'],
+        description = lambda w: config['builds'][w.build_name].get("description", "config/description.md"),
         lat_longs = config['lat-longs']
     output:
         auspice_json = "auspice/{build_name}_{segment}.json"
@@ -189,6 +190,7 @@ rule export_private:
             --include-root-sequence-inline \
             --lat-longs {input.lat_longs} \
             --auspice-config {input.auspice_config} \
+            --description {input.description} \
             --minify-json \
             --output {output.auspice_json} 2>&1 | tee {log}
         """

workflow/snakemake_rules/export.smk

@@ -65,6 +65,7 @@ rule export:
         metadata = build_dir + "/{build_name}/metadata.tsv",
         node_data = _get_node_data_by_wildcards,
         auspice_config = lambda w: config['builds'][w.build_name]['auspice_config'],
+        description = lambda w: config['builds'][w.build_name].get("description", "config/description.md"),
         lat_longs = config.get('lat-longs', "config/lat_longs.tsv"),
     output:
         auspice_json = "auspice/{build_name}_{segment}.json"
@@ -82,6 +83,7 @@ rule export:
             --include-root-sequence-inline \
             --lat-longs {input.lat_longs} \
             --auspice-config {input.auspice_config} \
+            --description {input.description} \
             --output {output.auspice_json} 2>&1 | tee {log}
         """