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diff --git a/microsetta_interface/templates/home.jinja2 b/microsetta_interface/templates/home.jinja2
index e346a652..8a6522f4 100644
--- a/microsetta_interface/templates/home.jinja2
+++ b/microsetta_interface/templates/home.jinja2
@@ -30,7 +30,7 @@
{% if request.args.get('project') == 'sbi' %}
{% else %}
-
+
{% endif %}
diff --git a/microsetta_interface/templates/new_results_page.jinja2 b/microsetta_interface/templates/new_results_page.jinja2
index 942aaf30..5e59dfad 100644
--- a/microsetta_interface/templates/new_results_page.jinja2
+++ b/microsetta_interface/templates/new_results_page.jinja2
@@ -479,14 +479,14 @@
break;
case "tmi-WGS-gut":
// Temporary workaround - we're going to add the Hadza study to the info['qiita-study-ids'] variable and alter the label to be more appropriate. Remove this line and the following four lines once contextual studies for WGS gut samples are fully restored.
- label = '{{ _('The Microsetta Initiative and Comparative Studies') }}';
+ label = '{{ _('the American Gut Project and Comparative Studies') }}';
span_id = "#dataset_links_tmi";
info['qiita-study-ids'].push("11358");
break;
case "tmi-16S-gut":
case "tmi-WGS-skin":
case "tmi-16S-skin":
- label = '{{ _('The Microsetta Initiative') }}';
+ label = '{{ _('the American Gut Project') }}';
span_id = "#dataset_links_tmi";
break;
case "multipop-16S-gut":
diff --git a/microsetta_interface/templates/nutrition.jinja2 b/microsetta_interface/templates/nutrition.jinja2
index 4648156c..e4f613ea 100644
--- a/microsetta_interface/templates/nutrition.jinja2
+++ b/microsetta_interface/templates/nutrition.jinja2
@@ -211,7 +211,7 @@
{{ _('Here, we\'re providing a measure of the diversity of your sample, and how it compares to the diversities of all of the same type of samples in The Microsetta Initiative. There are many ways to calculate diversity. For instance, you could compute a diversity value by counting the number of unique organisms observed (i.e., the sample "richness"). Or, you might be interested in weighting the calculation by the relative abundance of the organisms (i.e., the sample "evenness"). The metric we\'re computing here is called Faith\'s Phylogenetic Diversity (originally defined here). Faith\'s Phylogenetic Diversity computes the "richness" of your sample as the amount of evolutionary breadth represented by your sample. The way we compute alpha diversity is also through QIIME 2, and more information on it can be found in the alpha and beta diversity sections of the QIIME 2 tutorial') }}.
+{{ _('Here, we\'re providing a measure of the diversity of your sample, and how it compares to the diversities of all of the same type of samples in the American Gut Project. There are many ways to calculate diversity. For instance, you could compute a diversity value by counting the number of unique organisms observed (i.e., the sample "richness"). Or, you might be interested in weighting the calculation by the relative abundance of the organisms (i.e., the sample "evenness"). The metric we\'re computing here is called Faith\'s Phylogenetic Diversity (originally defined here). Faith\'s Phylogenetic Diversity computes the "richness" of your sample as the amount of evolutionary breadth represented by your sample. The way we compute alpha diversity is also through QIIME 2, and more information on it can be found in the alpha and beta diversity sections of the QIIME 2 tutorial') }}.
{{ _('Here we display how your sample fits in among the other samples of The Microsetta Initiative in terms of shared microbes. There are many ways to calculate beta diversity, differing in how to weight the distance between any two microbes. We take evolutionary distance into account with the metric displayed here, known as Unweighted Unifrac. You can find an overview of this metric here or better understand its derivation here. This computation is performed with QIIME 2, and more information on it can be found in the alpha and beta diversity sections of the QIIME 2 tutorial') }}.
+{{ _('Here we display how your sample fits in among the other samples of the American Gut Project in terms of shared microbes. There are many ways to calculate beta diversity, differing in how to weight the distance between any two microbes. We take evolutionary distance into account with the metric displayed here, known as Unweighted Unifrac. You can find an overview of this metric here or better understand its derivation here. This computation is performed with QIIME 2, and more information on it can be found in the alpha and beta diversity sections of the QIIME 2 tutorial') }}.