Merge branch 'main' of https://github.com/griffithlab/CIVIC_SVI_Course into main

Author: jhudsl-robot

docs/01-intro.md

@@ -3,6 +3,8 @@
 
 # Introduction
 
+This course is currently under development. The topics to be covered are outlined below.
+
 ## Motivation
 
 With the advent of massively parallel sequencing, millions of raw sequence reads can no be easily produced for a patient's tumor. Largely automated pipelines now exist to process these raw data, detect various types of molecular alterations (or variants), filter and review to identify high-confidence calls, and annotate these variants for functional significance. However, a major bottleneck remains at the variant interpretation stage. Genome analysts, molecular pathologists, clinical geneticists, laboratory geneticists and others are faced with a deluge of variants of potential relevance [@Good2014]. These variants must be manually reviewed and intersected with a vast ecosystem of knowledgebases and biomedical literature to provide current interpretation of their relevance for clinical application.

docs/index.html

@@ -164,7 +164,7 @@ <h1>
 </div>
 <div id="header">
 <h1 class="title">Introduction to Clinical Interpretation of Somatic Cancer Variants</h1>
-<p class="date"><em>May, 2023</em></p>
+<p class="date"><em>June, 2023</em></p>
 </div>
 <div id="about-this-course" class="section level1 unnumbered">
 <h1>About this Course</h1>

docs/index.md

@@ -1,6 +1,6 @@
 ---
 title: "Introduction to Clinical Interpretation of Somatic Cancer Variants"
-date: "May, 2023"
+date: "June, 2023"
 site: bookdown::bookdown_site
 documentclass: book
 bibliography: [book.bib, packages.bib]

docs/introduction.html

@@ -164,6 +164,7 @@ <h1>
 </div>
 <div id="introduction" class="section level1" number="1">
 <h1><span class="header-section-number">Chapter 1</span> Introduction</h1>
+<p>This course is currently under development. The topics to be covered are outlined below.</p>
 <div id="motivation" class="section level2" number="1.1">
 <h2><span class="header-section-number">1.1</span> Motivation</h2>
 <p>With the advent of massively parallel sequencing, millions of raw sequence reads can no be easily produced for a patient’s tumor. Largely automated pipelines now exist to process these raw data, detect various types of molecular alterations (or variants), filter and review to identify high-confidence calls, and annotate these variants for functional significance. However, a major bottleneck remains at the variant interpretation stage. Genome analysts, molecular pathologists, clinical geneticists, laboratory geneticists and others are faced with a deluge of variants of potential relevance <span class="citation">(<a href="#ref-Good2014" role="doc-biblioref">Good et al. 2014</a>)</span>. These variants must be manually reviewed and intersected with a vast ecosystem of knowledgebases and biomedical literature to provide current interpretation of their relevance for clinical application.</p>

docs/no_toc/01-intro.md

@@ -3,6 +3,8 @@
 
 # Introduction
 
+This course is currently under development. The topics to be covered are outlined below.
+
 ## Motivation
 
 With the advent of massively parallel sequencing, millions of raw sequence reads can no be easily produced for a patient's tumor. Largely automated pipelines now exist to process these raw data, detect various types of molecular alterations (or variants), filter and review to identify high-confidence calls, and annotate these variants for functional significance. However, a major bottleneck remains at the variant interpretation stage. Genome analysts, molecular pathologists, clinical geneticists, laboratory geneticists and others are faced with a deluge of variants of potential relevance [@Good2014]. These variants must be manually reviewed and intersected with a vast ecosystem of knowledgebases and biomedical literature to provide current interpretation of their relevance for clinical application.

docs/no_toc/index.html

@@ -164,7 +164,7 @@ <h1>
 </div>
 <div id="header">
 <h1 class="title">Introduction to Clinical Interpretation of Somatic Cancer Variants</h1>
-<p class="date"><em>May, 2023</em></p>
+<p class="date"><em>June, 2023</em></p>
 </div>
 <div id="about-this-course" class="section level1 unnumbered">
 <h1>About this Course</h1>

docs/no_toc/index.md

@@ -1,6 +1,6 @@
 ---
 title: "Introduction to Clinical Interpretation of Somatic Cancer Variants"
-date: "May, 2023"
+date: "June, 2023"
 site: bookdown::bookdown_site
 documentclass: book
 bibliography: [book.bib, packages.bib]

docs/no_toc/introduction.html

@@ -164,6 +164,7 @@ <h1>
 </div>
 <div id="introduction" class="section level1" number="1">
 <h1><span class="header-section-number">Chapter 1</span> Introduction</h1>
+<p>This course is currently under development. The topics to be covered are outlined below.</p>
 <div id="motivation" class="section level2" number="1.1">
 <h2><span class="header-section-number">1.1</span> Motivation</h2>
 <p>With the advent of massively parallel sequencing, millions of raw sequence reads can no be easily produced for a patient’s tumor. Largely automated pipelines now exist to process these raw data, detect various types of molecular alterations (or variants), filter and review to identify high-confidence calls, and annotate these variants for functional significance. However, a major bottleneck remains at the variant interpretation stage. Genome analysts, molecular pathologists, clinical geneticists, laboratory geneticists and others are faced with a deluge of variants of potential relevance <span class="citation">(<a href="#ref-Good2014" role="doc-biblioref">Good et al. 2014</a>)</span>. These variants must be manually reviewed and intersected with a vast ecosystem of knowledgebases and biomedical literature to provide current interpretation of their relevance for clinical application.</p>