Commit 37a0f1c2 authored by Hanna  JULIENNE's avatar Hanna JULIENNE
Browse files

fix key error

parent ede10f4b
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<p>
The JASS web interface allows for a fast derivation of multi-trait genome-wide association study (GWAS) summary statistics.
JASS can increase statistical power by leveraging pleiotropy, but also can deepen our understanding of SNPs functional effect (for a detailed explanation see the tab citation).
The current online version of JASS allows for a multi-trait GWAS from ~150 GWAS using the omnibus test (see next page for the complete list).
<p class="text-justify">
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 150 traits 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 XXXX SNPs 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.
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<AnalysisCard v-for="analysis in analysis" v-bind:key="analysis.title" v-bind:title="analysis.title" v-bind:description="analysis.description" v-bind:short_desc="analysis.short_desc" v-bind:link="analysis.link" />
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<h2> About </h2>
<p>
Jass is developed at Institut Pasteur by the <a href="https://research.pasteur.fr/en/team/statistical-genetics/">Statistical Genetics group</a> and the <a href="https://research.pasteur.fr/en/team/bioinformatics-and-biostatistics-hub/">Biostatistic and Bioinformatic HUB</a>
......@@ -40,7 +39,6 @@
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......@@ -80,7 +80,6 @@ blp_local_projects = Blueprint(
CORS(blp_local_projects)
def get_phenotypes():
return get_available_phenotypes(os.path.join(config["DATA_DIR"], "initTable.hdf5"))
......@@ -187,7 +186,7 @@ class ProjectGenomeFullMethodView(MethodView):
Fichier = "local_analysis_result.csv"
else:
Fichier = "genome_full.csv"
try:
return send_file(
Project(id=project_id).get_csv_path(),
......
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