e2867e617ae5d61bde6bf4cef1914825244ba645 dschmelt Thu Nov 18 09:54:21 2021 -0800 Announcing the Orphadata tracks refs #14319 diff --git src/hg/htdocs/goldenPath/newsarch.html src/hg/htdocs/goldenPath/newsarch.html index 55a4996..74ca043 100755 --- src/hg/htdocs/goldenPath/newsarch.html +++ src/hg/htdocs/goldenPath/newsarch.html @@ -38,44 +38,67 @@ </ul> </div> <div class="col-sm-3"> <ul> <li><a href="#2005">2005 News</a></li> <li><a href="#2004">2004 News</a></li> <li><a href="#2003">2003 News</a></li> <li><a href="#2002">2002 News</a></li> <li><a href="#2001">2001 News</a></li> </ul> </div> </div> </div> <!-- ============= 2021 archived news ============= --> +<a name="111821"></a> +<h2>Nov. 18, 2021 New Clinical Rare Disease track - Orphadata</h2> +<p> +We are happy to share another clinical resource for genetic disease correlation, +<a href="/cgi-bin/hgTrackUi?db=hg19&g=orphadata">the Orphadata track</a> from +<a target="_blank" href="https://www.orpha.net/">the Orphanet consortium</a>. This +track shows nearly 8000 genes, on hg19 and hg38, +annotated with human disorders and epidemiological information +including Human Phenotype Ontology (HPO) disorder name, association type, +modes of inheritance, age of onset, and age of death. This data +is gathered by a consortium of more than 40 countries, focusing +on rare diseases. This track includes gene-disease display filters +based on association type, inheretance mode, and age of inheritance. +</p> +<p> +Orphadata can be found on the Browser in the Phenotype and Literature +track group, natively interfacing with other UCSC Genome Browser +tools such as the JSON API, Table Browser, and Data Integrator. +We would like to thank the Orphanet team for providing this data. We +would also like to thank Chris Lee and Daniel Schmelter for the creation +and release of these tracks. +</p> + <a name="111721"></a> <h2>Nov. 17, 2021 Releasing A New Genome Browser Track Group: Single-Cell RNA-seq</h2> <p> We are excited to release a new Genome Browser track group with single-cell RNA-seq (scRNA-seq) datasets for the hg38 assembly. Data generated by scRNA-seq allows us to study the heterogeneity of cells in organs, explore gene expression at a cellular level, and track cellular states in both development and disease. <p class ="text-center"> <img class="text-center" src="../images/newsArchImages/scRNAseq.png" width="70%"></p> <p> We are starting with 14 scRNA-seq tracks covering different major organs of the body. Each new scRNA-seq track contains anywhere from 2-19 individual mRNA expression tracks in -<a target="_blank" href="https://genome.ucsc.edu/goldenPath/help/barChart.html">barChart</a> +<a target="_blank" href="/goldenPath/help/barChart.html">barChart</a> format. By default, tracks display gene expression per individual cell type annotation and are colored according to cell class:</p> <table cellpadding="2"> <thead> <tr> <th style="border-bottom: 2px solid;">Color</th> <th style="border-bottom: 2px solid;">Cell Classification</th> </tr> </thead> <tbody> <tr> <td style="background-color: #f0c000; padding-left: 20px"></td> <td>neural</td> </tr> <tr>