{% extends "minibase.html" %} {% block body %}

GPSEA cohort analysis

Successfully loaded {{ cohort | count | pluralize('individual') }}. {# Sex #} {{ cohort.count_males() | was_were }} recorded as male, {{ cohort.count_females() }} as female, and {{ cohort.count_unknown_sex() }} as unknown sex. {# Vital status #} {% if cohort | count == cohort.count_unknown_vital_status() %} No information about individuals' vital status was reported. {% else %} {{ cohort.count_alive() | was_were }} reported to be alive at the time of last encounter, {{ cohort.count_deceased() | was_were }} deceased, and vital status was unreported for {{ cohort.count_unknown_vital_status() | pluralize('individual')}}. {% endif %} {# Disease and age at last encounter #} {{ cohort.count_with_disease_onset() | pluralize('individual')}} had disease onset information and {{ cohort.count_with_age_of_last_encounter() }} had information about the age of last encounter.

{# Genotype & Phenotype #}
{# HPO terms #}

HPO terms

{% set distinct_hpos = cohort.count_distinct_hpo_terms() %} {% if distinct_hpos > 0 %} The cohort included {{ distinct_hpos | pluralize('distinct HPO term') }}. {% for count in hpo_counts %} {% endfor %}
{% if distinct_hpos > top_phenotype_count %} Top {{top_phenotype_count}} most common HPO terms. {% endif %} {% if n_has_onset_info %} {# Optional onset info #} {{ n_has_onset_info }} had onset information for at least 20% of individuals. {% endif %}
n HPO Term
{{ count['count'] }} {{ count['label'] }}
{% else %} No HPO terms were provided. {% endif %} {# The table is inconsistent. Skip it for now! {% if n_has_onset_info > 0 %}

Top {{top_var_count}} HPO Terms

A total of {{ cohort.count_distinct_hpo_terms() }} HPO terms were used to annotated the cohort.

{% for onset_info in has_onset_information %} {% endfor %}
HPO Count
{{ onset_info.display_label }} {{ onset_info.count }}
{% endif %} #}
{# Measurements #}

Measurements

{% set distinct_measurements = cohort.count_distinct_measurements() %} {% if distinct_measurements > 0 %} The cohort included {{ distinct_measurements | pluralize('measurement') }}. {% if distinct_measurements > top_phenotype_count %} Top {{ top_phenotype_count }} most common measurements. {% endif %} {% for count in measurement_counts %} {% endfor %}
n Measurement ID
{{ count['count'] }} {{ count['label'] }} {{ count['term_id'] }}
{% else %} No data regarding measurement assays were provided. {% endif %}
{# The most common diseases #}

Diseases

{% set distinct_diseases = cohort.count_distinct_diseases() %} {% if distinct_diseases > 0 %} The cohort members were diagnosed with {{ distinct_diseases | pluralize('disease') }}. {% if distinct_diseases > top_phenotype_count %} {% endif %} {% for count in disease_counts %} {% endfor %}
Top {{ top_phenotype_count }} most common diseases.
n Disease
{{ count['count'] }} {{ count['label'] }}
{% else %} No diagnoses were provided. {% endif %}
{# Genotype #} {# The most common variants #}

Variants

A total of {{ cohort.all_variant_infos() | count | pluralize('unique variant') }} were identified in the cohort. Variants were annotated with respect to {{ transcript_id }}.

{% for count in var_counts %} {% endfor %}

Top {{top_var_count}} variants

n Variant key HGVS Variant Class
{{ count['count'] }} {{ count['key'] }} {{ count['hgvsc'] }} ({{ count['hgvsp'] }}) {{ count['effects'] }}
{# The most common variant effects #}
{% if has_transcript %}

Variant effects

The effects were predicted for {{ transcript_id }}

{% for effect in variant_effects %} {% endfor %}
Variant effect Count
{{ effect['effect'] }} {{ effect['count'] }} ({{ effect['percent'] }}%)
{% else %}

Call this function with transcript to see table with variant effect counts.

{% endif %}
{% endblock %}