<h1class="main_title"> Joint Analysis of Summary Statistics </h1>
<pclass="main-intro">
<pclass="main_intro">
The JASS web interface efficiently compute multi-trait genome-wide association study (GWAS) and enable user to interacively explore results.
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).
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 <ahref="https://gitlab.pasteur.fr/statistical-genetics/jass_suite_pipeline">JASS pre-processing pipeline</a> and imputation of missing statistics has been conducted using the <ahref="https://gitlab.pasteur.fr/statistical-genetics/raiss">RAISS software</a>, resulting in a total of {{initmeta.nb_snps}} SNPs available for analysis.
<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 <ahref="https://gitlab.pasteur.fr/statistical-genetics/jass_suite_pipeline">JASS pre-processing pipeline</a> and imputation of missing statistics has been conducted using the <ahref="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.
</p>
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