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diff --git a/wqflask/wqflask/templates/tutorials.html b/wqflask/wqflask/templates/tutorials.html index 18f8d675..89143809 100644 --- a/wqflask/wqflask/templates/tutorials.html +++ b/wqflask/wqflask/templates/tutorials.html @@ -529,6 +529,30 @@ Registration: <a href="https://bit.ly/osga_2020-11-20">https://bit.ly/osga_2020- <td><iframe width="560" height="315" src="https://www.youtube.com/embed/4ZhnXU8gV44" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe> </tr> <!--WEBINAR ENDS HERE--> + + <!--NEW WEBINAR STARTS HERE--> + <tr> + <td><p><h3>Bonus 2 - Introduction to Gene Network</h3> + <p><i>Please note that this tutorial is based on GeneNetwork v1</i> + +<p>GeneNetwork is a group of linked data sets and tools used to study complex networks of genes, molecules, and higher order gene function and phenotypes. GeneNetwork combines more than 25 years of legacy data generated by hundreds of scientists together with sequence data (SNPs) and massive transcriptome data sets (expression genetic or eQTL data sets). The quantitative trait locus (QTL) mapping module that is built into GN is optimized for fast on-line analysis of traits that are controlled by combinations of gene variants and environmental factors. GeneNetwork can be used to study humans, mice (BXD, AXB, LXS, etc.), rats (HXB), Drosophila, and plant species (barley and Arabidopsis). Most of these population data sets are linked with dense genetic maps (genotypes) that can be used to locate the genetic modifiers that cause differences in expression and phenotypes, including disease susceptibility. + +<p>Users are welcome to enter their own private data directly into GeneNetwork to exploit the full range of analytic tools and to map modulators in a powerful environment. This combination of data and fast analytic functions enable users to study relations between sequence variants, molecular networks, and function.</p> + + <p>Presented by:<br> +Dr. Rob Williams<br> +Professor and Chair<br> +Department of Genetics, Genomics, and Informatics<br> +University of Tennessee Health Science Center +</p> +<!--<p>There is no fee associated with this webinar, but users are asked to register to receive the Zoom link and password. +Registration: <a href="https://bit.ly/osga_2020-11-20">https://bit.ly/osga_2020-11-20</a>--> +<!--<p>This webinar series is sponsored by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223). --> +</td> + <!--<td><strong>After the presentation, the recording will be made available here.</strong></td>--> + <td><iframe width="560" height="315" src="https://www.youtube.com/embed/B3g_0q-ldJ8" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe></iframe> + </tr> + <!--WEBINAR ENDS HERE--> </tbody> </table> </div> @@ -562,5 +586,6 @@ $('#myTable').DataTable(); </body> + {% endblock %} |