From 246d16e017f1291ea2270d07ef716d36778fb337 Mon Sep 17 00:00:00 2001 From: Rachel <rtorchet@pasteur.fr> Date: Fri, 22 Oct 2021 13:52:07 +0200 Subject: [PATCH] Update content --- client/assets/css/global.css | 1 - client/pages/index.vue | 14 ++++++++------ client/pages/phenotypes.vue | 7 +++---- 3 files changed, 11 insertions(+), 11 deletions(-) diff --git a/client/assets/css/global.css b/client/assets/css/global.css index ebeb0bc0..db428185 100644 --- a/client/assets/css/global.css +++ b/client/assets/css/global.css @@ -92,7 +92,6 @@ width: 75%; margin: 0 auto; padding: 30px 0px 30px 0px; - text-align: center !important; } .card-title { diff --git a/client/pages/index.vue b/client/pages/index.vue index facaef27..f79463c3 100644 --- a/client/pages/index.vue +++ b/client/pages/index.vue @@ -1,12 +1,14 @@ <template> <div> - <h1 class="main_title"> Joint Analysis of Summary Statistics </h1> + <h1 class="main_title"> Welcome to JASS v2.1, a web interface for the Joint Analysis of GWAS Summary Statistics</h1> <p class="main_intro"> - The JASS web interface efficiently compute multi-trait genome-wide association study (GWAS) and enable user to interacively explore results. - <br>JASS can increase statistical power by leveraging pleiotropy, but also can deepen our understanding of SNPs functional effect (for a detailed explanation see the citation box below). - <br>Currently this website host <b> {{initmeta.nb_phenotypes}} traits </b>available for analysis with the omnibus test. - All GWAS have been pre-processed using the <a href="https://gitlab.pasteur.fr/statistical-genetics/jass_suite_pipeline">JASS pre-processing pipeline</a> and imputation of missing statistics has been conducted using the <a href="https://gitlab.pasteur.fr/statistical-genetics/raiss">RAISS software</a>, resulting in a total of <b>{{initmeta.nb_snps}} SNPs</b> available for analysis. - To analyze data in your own facility and/or access supplementary joint analysis tests, please download and install the JASS python package. + The JASS web interface allows for a fast derivation of the joint tests of selected genome-wide association study (GWAS) summary statistics. The current version allows to perform two multivariate tests, + <ol><li>an omnibus K degree of freedom test, and </li> + <li>an 1 degree of freedom weighted sum of individual statistics with weights defined as the loadings of the first principal component of the genetic correlation matrix. </li> + </ol> + For more advance applications, please use the command line version. For details on the methodology, please refer to the citations below. + <br> + <br>The online version currently includes XXX publicly available GWAS classified into XX biological categories. All GWAS have been pre-processed using the <a href="https://gitlab.pasteur.fr/statistical-genetics/jass_suite_pipeline">JASS pre-processing pipeline</a> and imputation of missing statistics has been conducted using the <a href="https://gitlab.pasteur.fr/statistical-genetics/raiss">RAISS software</a>, resulting in a total of <b>{{initmeta.nb_snps}} SNPs</b>. </p> <v-container fluid> diff --git a/client/pages/phenotypes.vue b/client/pages/phenotypes.vue index 5fb317eb..71047fcc 100644 --- a/client/pages/phenotypes.vue +++ b/client/pages/phenotypes.vue @@ -2,13 +2,12 @@ <div> <div style="text-align:center; margin:30px;"> <h1> - Genome Wide Analysis - </h1> + Genome-wide analysis parameters</h1> <p style="width:80%; margin: 0 auto;"> - Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nulla vitae sapien at ante eleifend aliquet. Etiam cursus et ante non ultrices. Cras vel sollicitudin urna. Aliquam consectetur massa nec augue consequat, ac commodo est suscipit. Nulla sollicitudin risus eget orci feugiat vulputate. Maecenas ut feugiat massa. Nam euismod, augue a ullamcorper interdum, ipsum urna blandit nisl, cursus vehicula leo ante ac nisi. Sed semper pulvinar nisi ut dictum. In cursus velit nec eros sagittis aliquet. Donec interdum volutpat massa viverra fermentum. +Please select the traits you want to analyze jointly with the omnibus test. A research box to the right allows you to query our current database. The maximum number of trait that can be analyzed jointly is 64 traits. Computation time for a large number of trait can take up to half an hour. </p> </div> - <h2>List of phenotypes</h2> + <h2>Select the GWAS to be analyzed jointly:</h2> <div id="app"> <v-app> <v-data-table -- GitLab