{% extends "base-layout.html" %} {% block css %} {{ super() }} {% endblock %} {% macro errors_block() %} {% for error_description, error_content in errors %} {% if error_content %}
Sample | Group | Analyzed at | Sex according to sequence data | Average coverage [x] | |
---|---|---|---|---|---|
Chromosome X | Chromosome Y | ||||
{{ sample.sample }} | {{ sample.case }} | {{ sample.analysis_date.date() }} | {{sample.predicted_sex}} | {{ sample.x_coverage }} | {{ sample.y_coverage }} |
Sample | Average coverage[x] | {% for level_int, level_key in levels.items() %}Completeness {{ level_int }}x [%] | {% endfor %}
---|---|---|
{{ sample }} | {{ stats.mean_coverage|round(2) if stats.mean_coverage is defined }} | {% for level_int, level_key in levels.items() %}{{ stats[level_key] if stats[level_key] is defined }} | {% endfor %}
Sample | Fully covered {{ interval_type }} [%] | Incompletely covered {{ interval_type }} | ||
---|---|---|---|---|
{{data[0]}} | {% if data[1] == 100.00 %}No incompletely covered intervals. | {% else %}{{ data[1] }} | {{ data[2] }} | {% endif %}
Chanjo2 was used for coverage analysis based on reads alignment. Chanjo2 computes coverage and coverage completeness using an internal module based on d4tools. The genome has been analyzed at the {{ extras.interval_type }} level, for genes defined at HGNC.
{% if extras.panel_name %}Final coverage metrics were calculated for genes from the clinical panels. Note that estimations were made regarding coverage and completeness on the level of {{ extras.interval_type }}.
{% endif %}Completeness: defined as the ratio of bases sequenced deeper than a specified cutoff e.g. 10x
Gene/Transcripts/Exons coverage: defined as the ratio of these intervals are fully covered ('i.e. with a completeness of') 100% 'at' {{ extras.default_level }}x.
Gender prediction from data: calculated by comparing relative chromosome coverage (X/Y). Some reads randomly map to the Y chromosome. Therefore, a less than 10 fold difference is used to infer a "male" sample.
{% endmacro %} {% block title %}Based on gene panel: {{ extras.panel_name }}
{% endif %} {{ sex_rows_block() }}